Academic Model Answers Library — Megaminds (UK Postgraduate)

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Managing the Global Supply Chain and Sustainability 2,500 words

Managing the Global Supply Chain and Sustainability – Individual Company Case Analysis

This assessment is an individual company case analysis for the Level 7 module Managing the Global Supply Chain and Sustainability. Students are required to select a real organisation of any size, type, industry or country and produce a comprehensive analysis of one operations performance objective. The available performance objectives are cost, dependability, flexibility, speed and quality. The report should identify current issues faced by the chosen organisation in relation to the selected objective and critically analyse the factors affecting its performance. Students are expected to apply relevant theories, concepts and tools covered during lectures and seminars to the selected company case. Rather than providing only descriptive explanations of theoretical concepts, the assessment requires students to demonstrate how these concepts can be applied to understand the organisation's operational or supply chain challenges. The analysis should consider how relevant theories, models or tools could contribute to improving the company's performance. The report should also provide a critical discussion of appropriate performance-improvement practices. These may include the use of digital technologies, sustainability practices, supply chain strategies, operational approaches or other relevant methods. Students should relate these practices directly to the findings from their chosen company case and consider their practical implications. Academic evidence and real-world examples should be used to support the analysis, with appropriate attention given to supply chain and operations management literature. The assessment is designed to develop students' ability to understand supply chain strategies, assess their contribution to agility, viability and sustainability, propose practical solutions to modern logistics and supply chain challenges, and evaluate how digital technologies and sustainability practices can improve supply chain performance. The report should therefore demonstrate analysis, application of theory, critical evaluation and evidence-based recommendations rather than simply describing the organisation or its supply chain. The individual report has a maximum length of 2,500 words, excluding references, tables, figures and appendices. It must include a contents page, be spell-checked and follow the specified formatting requirements. The report should use Arial 12-point font, 1.5 line spacing, A4 page size and 2.54 cm margins. Academic sources such as journal articles and books should be used, and all sources cited within the report must appear in a Harvard-style reference list. The report is submitted through Moodle Turnitin as a Word document.

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Machine Learning on Big Data 3,000 words

Machine Learning on Big Data using PySpark

This group assessment for the Machine Learning on Big Data module requires students to apply machine learning techniques to a large real-world dataset using PySpark DataFrame and Spark ML. The coursework is designed to develop practical understanding of big data processing, machine learning implementation, model optimisation and evaluation. Students work in groups of three or four and complete a machine learning project using a suitable large dataset obtained from a benchmarking source such as Kaggle, their workplace or another valid resource. The recommended dataset size is between 300 MB and 1 GB. The main task requires students to select a dataset containing multiple classes rather than a binary classification problem and develop an appropriate machine learning solution. The project begins with loading and preprocessing the data using PySpark DataFrame. Students are expected to address issues such as missing values, data normalisation, feature engineering and class imbalance. For text datasets, additional preprocessing techniques such as stemming, lemmatisation and TF-IDF may be applied. Students must then select and implement an appropriate machine learning method using PySpark MLlib or the Spark ML package. The brief permits approaches including multiclass classification, clustering, ensemble learning and text mining. Model parameters must be optimised using techniques such as grid search or random search. Students are required to evaluate their trained models using suitable metrics, including accuracy, F1-score, precision, recall and classification matrices where appropriate. The brief encourages students to maintain model accuracy and robustness above 90% for the highest possible mark and to discuss steps taken to address bias and variance. The results must be visualised or printed clearly, with appropriate interpretation and analysis of the findings. Students must also consider Legal, Social, Ethical and Professional (LSEP) issues throughout the project. Each student selects one LSEP principle and discusses relevant concerns such as dataset bias, privacy or ethical implications, together with suitable mitigation strategies. The final report should be approximately 3,000 words with a tolerance of ±10% and submitted as a single HTML report using the template provided on the module Moodle site. The report should consolidate the individual contributions of all group members into one comprehensive and user-friendly analytics report. The main assessment is weighted 60% for the report and 40% for the group presentation. The presentation is conducted online through Microsoft Teams, and all group members must participate. The assessment evaluates understanding of Spark, preprocessing, modelling, optimisation, evaluation and the ability to explain and interpret the implemented solution.

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Business Consultancy Project 5,000 words

Business Consultancy Project – Summative Coursework

This assessment requires students to complete a 5,000-word Business Consultancy Project designed to replicate the work of a professional consultant. The project accounts for 100% of the module assessment and requires students to investigate a clearly defined business issue, challenge or problem identified in the earlier Consultancy Project Proposal. Students must use the same client, topic and issue proposed in the previous submission unless a change has been strongly recommended through feedback or endorsed by the supervisor or tutor. The consultancy project requires deep and independent research using credible secondary sources, including recent peer-reviewed academic journals, industry reports and reputable business publications. The analysis should translate evidence into meaningful insights and actionable recommendations that create strategic value for the client organisation. The report must critically analyse the selected business problem rather than simply describe the organisation or relevant theories. The report should contain an Executive Summary, Introduction, Company/Client Overview, Problem Definition and Consultancy Focus, Stakeholder Analysis, Data Analysis and Framework Application, Recommendations and Conclusion, and a 500-word Employability Reflection. The Data Analysis and Framework Application section carries the largest indicative allocation at approximately 1,800 words and requires students to apply two or three relevant models or frameworks. Examples provided in the brief include SWOT, PESTLE, Porter’s Five Forces and the Balanced Scorecard. Students are also expected to present and interpret secondary data using appropriate tables, charts, Excel outputs or pivot tables. The Recommendations and Conclusion section should provide three actionable and prioritised recommendations supported by evidence, while considering implementation risks, barriers and anticipated benefits. The Employability Reflection should consider research, analytical, problem-solving, project management and communication skills, together with teamwork, leadership, ethical awareness, sustainability, personal development, career relevance and future professional growth. The assessment requires Harvard referencing throughout. The report should use professional formatting, third-person academic writing, numbered pages, correctly labelled tables and figures, and accurate in-text citations and references. The brief emphasises the use of recent and credible sources, with the majority of references expected to come from publications within the previous 6–12 months.

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Global Engineering: Theory and Practice 3,000 words

Global Engineering: Theory and Practice – Aspen Pharmacare Global Expansion and Environmental Sustainability

This assessment for the Global Engineering: Theory and Practice module requires students to prepare a critical report examining the international growth strategies and future sustainability of a global pharmaceutical company. The assessment is based on the published case study “The growth strategies of a global pharmaceutical company: a case study of Aspen Pharmacare Holdings Limited” by Victoria Margaret Hodgon and Muhammad Ehsanul Hoque. The scenario requires students to act from a management perspective, where a pharmaceutical company is considering international expansion while maintaining environmental sustainability as one of its core business values. The report has a maximum length of 3,000 words, excluding the reference list, and must critically address the success and growth strategy of Aspen Pharmacare as presented in the selected research paper. Students are expected to demonstrate understanding of international business and global engineering concepts while evaluating the strategic choices made by the company. The report should not simply reproduce the findings of the source paper; instead, it should critically evaluate the evidence, identify strengths and weaknesses, consider challenges and risks, and use additional published literature to inform management decisions. The first section is a 250-word summary explaining the approach used in the report to describe Aspen Pharmacare’s success and presenting the key findings. The introduction, limited to 500 words, should provide the background context of the global pharmaceutical industry and explain the main growth strategies available to a global pharmaceutical company. This section establishes the context for understanding Aspen’s international development. The main evaluation section accounts for 1,500 words and requires a critical assessment of Aspen Pharmacare’s roadmap to global success, including its growth strategies and strategic planning. Students should examine the different approaches used by the company and consider the benefits, limitations, challenges, risks and strategic trade-offs associated with its growth. The analysis should demonstrate critical strategic evaluation rather than simply describing the company's historical development. The future prospects section, limited to 500 words, focuses particularly on sustainability. Students must identify the key area affecting Aspen’s future sustainability in light of the challenges associated with its growth and consider what additional actions could be taken in environmental sustainability. Students are also required to locate and use published literature beyond the main Aspen Pharmacare paper to inform management about future trends and developments. The report concludes with a 250-word conclusion containing recommendations for management based on the findings of the analysis. The recommendations should be specific, relevant to the company's circumstances and supported by the evidence discussed in the report. Alternative strategic options should also be considered where appropriate. Harvard referencing is mandatory. The report should be professionally presented with appropriate headings, a logical structure, clear and coherent language, correct grammar and punctuation, and effective integration of academic evidence. The assessment is worth 100% of the module and is evaluated on the quality of the summary, introduction, strategic evaluation, future sustainability analysis, conclusions and recommendations, referencing and overall professionalism.

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Problem Solving and Research Methods for Managers 1,000 words

Problem Solving and Research Methods for Managers – Summative Assignment

This module assessment develops students’ ability to apply problem-solving tools, techniques and research methods to an original business problem. The assessment consists of two summative components. Summative 1 comprises two 25-question multiple-choice questionnaires covering the key learning areas taught throughout the module. Summative 2 consists of a video presentation and an individual reflective piece. For the video presentation, students must prepare a 10-to-15-minute presentation demonstrating competent application of the problem-solving tools, techniques and research methods taught during the module. The presentation should address an original problem identified within a business where the student has previously worked or currently works. Where the student does not have relevant work experience, a business that the student is interested in working for in the future may be selected. The presentation should include an appropriate analysis of the problem, application of relevant problem-solving and research methods, conclusions and recommendations. References should be included at the end of the presentation using the Harvard referencing system. The second component is an individual reflective piece of 1,000 words. The reflection should document the student’s learning experience, the outcomes of the experience and how the learning will inform future professional practice. The assessment brief emphasises that reflective writing should go beyond simply describing events. Students are expected to explore their thoughts and emotions and develop deeper self-awareness. The use of one or more reflective or learning frameworks is recommended to structure the reflection. The assessment is designed to assess both practical application and reflective learning. The video presentation should demonstrate the ability to connect theory with a real or relevant business problem and produce appropriate conclusions and recommendations. The reflective component should demonstrate what the student has learned from the experience, how that learning has influenced their understanding and how it can be transferred to future practice. Students must use Harvard referencing. The assessment is submitted through the relevant Moodle/Turnitin or Panopto submission links. The assessment brief states that presentation references are not included in the presentation word count. Students should also ensure that their final submission follows the required file-format and deadline instructions provided on Moodle. The marking rubric places substantial emphasis on the quality of presentation design and delivery, the depth of reflection and learning demonstrated, and clarity of writing, structure, grammar, Harvard referencing and use of visuals. Strong work should therefore demonstrate a clear connection between the business problem, the selected problem-solving and research methods, the resulting analysis, conclusions and recommendations, followed by a genuinely reflective discussion of the learning experience and its implications for future practice.

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Strategic Management in Healthcare 4,000 words

Strategic Management in Healthcare – Strategic Analysis and Strategy Formulation

This individual summative assessment for the Strategic Management in Healthcare module requires students to critically examine strategic management and strategic thinking within a healthcare organisation, hospital, clinical department or healthcare unit of their choice. The assessment is designed to develop students’ ability to apply strategic management concepts and analytical frameworks to a real healthcare setting, evaluate the internal and external factors affecting organisational performance, and formulate appropriate strategies in response to identified operational and competitive challenges. The assessment consists of a 4,000-word report with a 10% tolerance and accounts for 100% of the module assessment. Students must first select an organisation, clinical department or healthcare unit to use as the case setting. The report should begin with a concise introduction to the selected case setting, establishing its organisational context and providing a clear direction for the strategic analysis. The introduction should explain the relevant characteristics of the organisation or healthcare unit and provide sufficient background to understand the strategic issues examined in the report. The report must critically analyse the relevance of strategic management and strategic thinking to the selected healthcare setting. Rather than simply describing strategic management concepts, students are expected to explain why strategic planning and strategic thinking are important for the particular organisation or department and how they can support performance improvement, service development and responses to operational and competitive challenges. A central requirement is the application of three strategic analysis tools or frameworks. The assessment examples include SWOT, PESTLE, Balanced Scorecard, Value Chain, Porter’s Five Forces, Resource Based View and Blue Ocean Strategy. Students must apply at least one appropriate tool at each of three analytical levels: macro-environment analysis, service area or market analysis, and internal environment analysis. Before applying each tool, students should define the framework and critically justify why it is relevant, effective and suitable for the selected healthcare case setting. The analysis should be detailed and evidence-based rather than purely descriptive. Students are then required to develop a hierarchy of strategies based on the findings from the strategic analysis. Strategies should be formulated at three levels and should clearly respond to the issues identified through the external, market or service-area and internal analyses. The report should explain how the proposed strategies could help the healthcare organisation or unit improve performance and address its operational and competitive challenges. The relationship between the analysis, strategic recommendations and expected outcomes should be made explicit. The final component requires students to reflect on the relevance and usefulness of the strategic tools beyond the selected case study and in relation to their current or future professional role. The reflection should consider how the strategic frameworks and analytical approaches could be transferred to other organisational or professional situations. The assessment should use appropriate evidence from sources such as academic journal articles, books, websites, case studies and grey literature. Harvard referencing is required. The marking criteria place emphasis on the quality of the introduction and case context, critical discussion of strategic planning, quantitative and analytical application of three strategic tools, strategy formulation and evaluation, reflection on application relevance, and presentation and referencing. The assessment therefore requires an integrated connection between the healthcare case, strategic analysis, evidence, recommendations and reflection rather than isolated descriptions of strategic frameworks.

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Advanced Research Topics

Generative Adversarial Networks – Building and Applying GANs to Real-World Problems

This individual assessment focuses on building and understanding Generative Adversarial Networks (GANs) and applying them to real-world problems across different domains. The assignment is based on the GAN topics covered in Unit 5 and requires students to implement GAN models, analyse their behaviour, generate synthetic data and critically evaluate the quality of the generated outputs. The assessment consists of two main parts: building and understanding GANs from scratch using synthetic two-dimensional data, followed by applying GANs to three real-world application areas involving medicine, cybersecurity and creative artificial intelligence. Part 1 focuses on developing a practical understanding of GANs through implementation using PyTorch and synthetic 2D data. Students must first reproduce the sine-wave GAN demonstrated in the tutorial. They then create and model a new two-dimensional distribution, selecting from a 2D spiral, a mixture of Gaussians, or a noisy parametric curve defined as y = sin(2x) + 0.3cos(5x) + epsilon. Students must modify the GAN architecture, for example by changing the activation function or layer depth, and visually compare the original data distribution with the generated samples. This section is intended to reinforce understanding of the generator, discriminator, GAN training process and the effect of architectural choices on generated data. Part 2 addresses three real-world GAN applications. The first application concerns optical coherence tomography (OCT) retinal images using the OCTMNIST subset of MedMNIST. Students must explore the dataset, examine class distributions and sample images, build a ConvNet-based Deep Convolutional GAN (DCGAN) using PyTorch or TensorFlow/Keras, train the model and track generator and discriminator losses. Generated retinal images must be compared with real images both visually and quantitatively, using a performance measure such as the Fréchet Inception Distance (FID). An optional extension involves implementing a conditional GAN and demonstrating generation of images for specific classes. The second application focuses on cybersecurity using the preprocessed CICIDS2017 dataset containing DDoS and benign network traffic. Students must combine the relevant data files, explore the dataset and understand its features and class balance. A GAN must be developed to generate synthetic feature vectors rather than images. The model should be trained using benign and DDoS attack data, training loss curves should be monitored, and PCA or t-SNE should be used to visualise and compare real and generated feature distributions. The quality of the synthetic data should then be evaluated. An optional extension involves expanding the analysis to the full CICIDS2017 dataset and examining generalisation across different attack types. The third application focuses on Creative AI using the QuickDraw birthday cake category. Students must explore the birthday cake sketch dataset and implement a ConvNet-based GAN (DCGAN) to generate realistic birthday cake sketches. Generated sketches should be evaluated visually and quantitatively, including comparison with real examples and an appropriate metric such as FID. An optional extension involves generating samples from additional QuickDraw categories and discussing how model performance changes across different classes and levels of sketch complexity. The submission consists of both code and a written report. The code accounts for 60% of the assessment and must complete the required modelling tasks, present generated samples, compare generated and real data, use appropriate functions and include clear annotations so another user can understand the implementation. The report accounts for 40% and must be 6–8 pages. It should explain the analytical steps undertaken, justify the selected approaches, provide brief descriptions of the models used, interpret the results and include appropriate figures, evaluation metrics and academic references. The report should critically discuss why particular network architectures were selected rather than simply providing textbook definitions.

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German Electricity Load Forecasting Using Time Series and Machine Learning Models

This individual assessment focuses on analysing and forecasting German electricity load using time-series analysis, statistical forecasting models and machine-learning approaches. Students are required to work with publicly available electricity data from the Open Power System Data platform and investigate the characteristics of the German time series before developing and comparing a range of forecasting models. The project combines exploratory data analysis, time-series modelling, regression-based forecasting and neural-network modelling, with particular emphasis on critical evaluation of modelling choices and forecast performance. The first stage requires students to retrieve the 60-minute electricity data and isolate the German data using the country identifier “DE”. The data should be aggregated into weekly and daily values using tools such as Pandas, with observations retained from 1 January 2015 through October 2020. Students must produce initial plots and conduct exploratory data analysis to identify the main components of the time series, including possible trend and seasonal patterns. Time-series analysis should then be performed to investigate and test for non-stationarity. The modelling component begins with benchmark forecasting methods such as Mean, Naive, Seasonal Naive and Drift forecasts. Students are required to use a two-year forecast horizon and compare the performance of these benchmark approaches. An autoregressive modelling approach must then be developed using SARIMA where appropriate. Students must identify suitable model parameters using the AIC likelihood method, considering the required combinations of p, d, q, P, D and Q parameters. Model fit should be assessed through residual analysis, including inspection of residual distributions and autocorrelation plots. Forecasts should include confidence intervals and performance should be evaluated using suitable metrics such as RMSE. The assessment also requires an exogenous temperature variable to be incorporated into a SARIMAX model. Berlin is specified as the representative location for German temperature data. Students must recognise the distinction between a true operational forecast and an explanatory or conditional forecast when future observed temperature values are used. The temperature variable should also be used to produce weekly forecasts. Further modelling requires students to apply a feature-based regression model, such as Random Forest or Gradient Boosting Regression, to the weekly electricity-load and temperature data. The final modelling stage uses hourly data with a Long Short-Term Memory (LSTM) neural network. Students must conduct a literature review relating to LSTM applications for the forecasting task, build and tune the model, evaluate its performance and forecast the final two years of available data. The report must critically compare the models rather than simply present numerical results. Students must address specific questions concerning improvement over the Seasonal Naive benchmark, prevention of data leakage when constructing temperature lag features, SARIMAX parameter choices, the value and availability of temperature and holiday covariates, and the relative interpretability and complexity of SARIMAX, feature-based and neural-network models. Students must also recommend one model for operational use based on accuracy, uncertainty, interpretability and maintenance considerations. The final report should be 6–8 pages and include model forecast plots, an evaluation-metrics comparison table, critical discussion of the results, comparison with real data, future improvements and appropriate references. Students must also create a GitHub repository containing the codebase and follow appropriate coding practices. The submitted code must reproduce the figures, models and numerical values presented in the report.

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International Business 2,500 words

Literature Review – International Business Research

This assessment is a 2,500-word individual Literature Review for the International Business module. The assignment requires students to select an international business-related research topic, develop a suitable research question and critically examine existing academic literature relevant to the proposed area of research. The purpose of the assessment is to demonstrate knowledge of the selected subject area, evaluate existing research, identify important debates and inconsistencies, examine research methodologies and theoretical frameworks, and establish a clear research gap that can provide the basis for further investigation. Students must obtain tutor approval for their chosen research topic before completing the Literature Review. The selected topic should have clear relevance to international business and should address an issue that is academically significant and practically relevant. Students are expected to use high-quality academic sources, with particular emphasis on peer-reviewed journal articles. The assessment guidance expects students to critically discuss a minimum of five and a maximum of eight journal articles, although additional academic sources may be used to support the discussion and critique. The Literature Review consists of three main sections: Introduction, Literature Analysis and Conclusion. The Introduction should be approximately 300 words and should introduce the research topic, explain why the issue is important, establish the main research question and demonstrate its relevance to international business. Students should also briefly discuss the potential implications of the proposed research for the advancement of knowledge, theory and practice. The Literature Analysis should be approximately 1,900 words and forms the main part of the assessment. Students should move beyond simply describing individual articles and instead analyse, evaluate and synthesise the literature. For each selected journal article, students should consider its contribution to existing knowledge, theoretical frameworks, research methodology, suggested research gaps and relationship to the proposed research question. The literature should be compared and contrasted to identify areas of agreement, disagreement, methodological differences, theoretical differences and unresolved issues. The analysis should demonstrate critical engagement with the literature rather than providing separate descriptive summaries of each source. The Conclusion should be approximately 300 words and should bring together the major agreements, disagreements and themes identified in the literature. Students should use the conclusion to justify their proposed research by demonstrating how it can address one or more of the research gaps identified through the literature review. The assessment is worth 100% of the final module grade and requires Harvard-style referencing. Students must provide a complete reference list and ensure that sources are appropriately acknowledged throughout the review. The assessment criteria evaluate knowledge of the subject area, analysis of research and methodologies, critical evaluation of literature, communication of complex ideas and professional referencing. High-quality work is expected to demonstrate a well-defined international business topic, strong critical analysis, comparison and synthesis of academic literature, clear identification of a research gap and a logically justified direction for future research.

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Research Methods

Assignment 3 – Large Language Models: LLM Coding and Report

This individual assessment for the Research Methods module focuses on the application of Large Language Models (LLMs) to a practical data science problem. The assignment is worth 25% of the module and is designed to develop students’ knowledge and understanding of research methods, investigative planning, data analysis, model evaluation and effective technical communication. Students are required to complete both a coding component and a concise written report demonstrating how an LLM has been selected, trained or fine-tuned, applied to a suitable task and evaluated against an appropriate baseline. The assessment begins with familiarisation with relevant literature. Students are expected to investigate the history and development of their chosen problem and examine the methods that have previously been used to address it. The brief provides key papers on common types of LLMs as a starting point for the literature review. Students then select a task that can be addressed through fine-tuning an LLM, with examples including sentiment analysis, fake news detection and topic classification. A publicly available dataset suitable for the selected text-classification problem must also be identified. Suggested sources include Kaggle and Hugging Face Datasets. The data must be appropriately preprocessed, including tokenisation using BERT's tokenizer and division into training and testing sets. Students then fine-tune a pre-trained BERT or BERT-style model using suitable tools such as the Hugging Face Transformers library and PyTorch. Possible model choices include BERT, RoBERTa and T5. The selected model should be appropriate for the specific problem, recognising that different language models may perform differently across tasks. Students are expected to implement a suitable training process using an appropriate optimiser and loss function. Model performance must be evaluated using relevant classification metrics, including accuracy, precision, recall and F1-score. The performance of the selected LLM should also be compared with a baseline model, such as Logistic Regression, Naive Bayes or a pre-trained BERT model. The analysis should explain the results and consider their relevance to the chosen problem. Two main submission components are required. The first is a code notebook, such as a Jupyter or Google Colab notebook, containing annotations explaining the purpose and operation of the relevant code so that another person can understand and reproduce the work. The second is a report of no more than three pages, including appropriate figures, tables and references. The report should cover the motivation and dataset, methodology, model training and evaluation, results and discussion, limitations, conclusion and possible future improvements. The assessment rubric places particular emphasis on coding quality and implementation, model architecture, analysis and interpretation, and report presentation. Strong work should demonstrate well-structured and reusable code, clear explanation of the model architecture and configuration, appropriate evaluation metrics and visualisations, meaningful comparison with relevant literature or baseline models, and critical evaluation of the model's success and possible improvements.

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Global Strategic Management 3,500 words

Global Strategic Management – Linear to Circular Business Model Transformation

This assessment for the Global Strategic Management module examines how organisations can transform from traditional linear business models towards circular business models. Students must select one of four approved organisational cases and use the same case consistently across both summative assessments. The approved cases are SKF, focusing on servitisation and remanufacturing transformation; Sandvik, focusing on closed-loop materials and tool recovery; Volvo Construction Equipment, focusing on design for remanufacturing and lifecycle optimisation; and Husqvarna, focusing on access-based and circular consumer models. The assessment requires students to apply strategic management, sustainability and circular economy concepts to evaluate the transformation of the selected organisation. Assessment A is a Strategic Poster worth 30% of the overall module mark. The poster should visually and analytically map the transformation of the selected organisation from a linear to a circular business model. It contains three main components. First, students must identify and analyse external drivers using PESTEL, explaining the factors creating pressure or opportunities for circular transformation. Second, students must explicitly reconfigure the organisation's value chain, distinguishing between primary activities such as inbound logistics, operations, outbound logistics, marketing and sales, and service or lifecycle activities, and supporting activities such as firm infrastructure, human resource management, technology development and procurement. Third, students must identify one core structural strategic tension created by the transition. This tension should represent a built-in trade-off in which improving one strategic objective may constrain or challenge another. Assessment B is a Strategic Evaluation Report worth 70% of the overall module mark. The report has a word limit of 3,500 words with a 10% tolerance, excluding the table of contents, reference list and appendices. The report requires a comprehensive strategic evaluation of the selected organisation's transition from a linear to a circular business model and should integrate concepts and frameworks covered throughout the module. The first component of the report requires a Business Model Reconfiguration Analysis using the Business Model Canvas. Students should critically analyse how the circular transformation changes the organisation's value proposition, customer segments, customer relationships, channels, key activities, key resources, key partnerships, revenue streams and cost structure. The analysis should explain how value is created, delivered and captured differently under the circular model. The second component evaluates sustainability and legitimacy using an integrated analysis of the Triple Bottom Line, SAFe framework and stakeholder power and interest analysis. Students should assess economic, environmental and social sustainability, evaluate the suitability, acceptability and feasibility of the transformation, and identify stakeholders who can enable or constrain implementation. The third component requires students to analyse the same strategic tension identified in the poster. The tension should be evaluated in greater depth using appropriate strategic, sustainability and stakeholder frameworks, followed by a theoretically grounded and operationally feasible recommendation. The final component requires students to integrate four of their strongest reflective blog posts from the twelve seminar weeks. The reflection should demonstrate intellectual development, critical thinking, engagement with theory, seminar participation and responsiveness to tutor feedback rather than simply describing the content of the seminars. The assessment is expected to demonstrate Level 7 academic standards through integrated framework application, critical evaluation, strategic judgement and advanced reflective insight. Academic sources must be cited using Harvard referencing, with appropriate in-text citations and a complete reference list.

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Financial Performance Management 3,500 words

Financial Performance Management – Financial Performance, Balanced Scorecard and Integrated Reporting

This individual assessment for the Financial Performance Management module requires students to produce a comprehensive analysis of the financial and non-financial performance of an international organisation and its closest competitor. The assessment is designed to develop students’ ability to evaluate organisational performance using financial analysis techniques, critically assess strategic performance-management frameworks, and examine the benefits and challenges associated with Integrated Reporting. The report has a maximum length of 3,500 words, with a 10% tolerance, excluding references, tables, figures and appendices, and accounts for 100% of the summative assessment. The first part of the report focuses on financial performance using ratio analysis. Students must select an international organisation as Company A and identify its closest competitor as Company B. The competitor should be selected using appropriate criteria, including comparable operating activities, industry, country and financial characteristics. Students are expected to obtain financial statements covering at least the most recent two years available for analysis. The ratio analysis should cover a broad range of areas, including liquidity, working capital cycle, profitability, leverage and valuation. Students should calculate and interpret relevant ratios, compare performance between the two organisations and across different years, and critically discuss the overall financial position. Input data and calculations may be presented in the main report or appendix, supported by appropriate tables and graphs. The second part examines Kaplan and Norton’s Balanced Scorecard as a Strategic Management System. Students must critically evaluate the relevant Balanced Scorecard literature and consider whether the traditional model remains appropriate in contemporary business environments. The report should discuss possible limitations or areas for improvement and then develop a proposed Balanced Scorecard specifically for Company A. The proposed scorecard should be linked to the organisation’s strategy and vision and should identify suitable objectives, measures and critical success factors. The third part focuses on Integrated Reporting. Students must critically analyse the potential benefits and challenges of adopting Integrated Reporting for Company A, using relevant academic literature and the International Integrated Reporting framework. The discussion should consider how Integrated Reporting combines financial, non-financial, historical and forward-looking information and how it can help stakeholders understand an organisation’s use of resources and prospects for long-term sustainable success. The report should follow an appropriate academic structure, including an introduction, financial performance analysis, Balanced Scorecard analysis, Integrated Reporting analysis and conclusion. Harvard referencing is required, supported by a comprehensive range of relevant academic and professional sources. The recommended structure allocates approximately 1,000 words to each main question, with approximately 250 words for the introduction and conclusion.

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Business Research Methods 3,500 words

Business Research Methods – Research Methodologies, Research Instrument and Research Dissemination

This individual assessment for the Business Research Methods module requires students to produce a structured report of no more than 3,500 words. The assessment is designed to develop students’ ability to identify and justify a suitable business research problem, critically evaluate research methodologies, design an appropriate research instrument, and consider how potential research findings could be effectively communicated to relevant audiences. The report consists of three interconnected sections that require students to demonstrate critical research skills and an understanding of how research can contribute to knowledge and practical decision-making. Section 1 focuses on comparing two research methodologies. Students select a topic of interest or a business problem relevant to their degree specialism, such as strategy, supply chain management, international business and economics, marketing, finance, or human resources. They first explain and justify the selected research problem and formulate a research question. Students then review relevant academic literature, justify the selection of key readings, and demonstrate the scope of the literature through a visual presentation such as a mind map, Venn diagram, or literature map. The section concludes with a detailed critical evaluation of at least two established research methodologies, considering their application, contribution to theory and research, advantages, limitations, constraints, and potential research gaps. Section 2 focuses on the development of a research instrument. Students design an appropriate instrument for their proposed research, such as an interview guide, survey questionnaire, or another suitable data-collection tool. The instrument is provided in an appendix, while the main report includes a reflection explaining how and why it was designed. Students are not required to collect data for this assessment. The section concludes by evaluating the expected value of the proposed instrument and its potential contribution to answering the research question. Section 3 addresses research dissemination. Students identify the audiences that could benefit from the potential research findings and explain why those audiences are relevant. They also consider appropriate methods of communicating research outcomes, including suitable summaries, media, report design, and potential partners such as public organisations, NGOs, associations, or industry. The assessment requires Harvard referencing and a bibliography containing at least 12 relevant journal articles, including at least six published within the previous 24 months. The report is assessed on the clarity of the research problem, depth of literature analysis, critical evaluation of research methods, quality of the proposed research instrument, understanding of research dissemination, and overall academic presentation.

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Fundamentals of Digital Technologies

Fundamentals of Digital Technologies – Group Project and Individual Refinement

This assessment is a project-based assignment for the DG4FDTL Fundamentals of Digital Technologies module. It is designed to develop students' practical understanding of digital technologies by combining mathematical concepts, programming, algorithms, data analysis and learning methods within a real-world project. The project is structured around a common group component, known as the Group Trunk, and an individual component in which each student develops a specialised refinement of the shared project. The project topics are designed around key areas covered by the module, including linear algebra, calculus, probability, learning algorithms, algorithms and Python programming. Students work in groups to establish a common project foundation and then develop an individual refinement that extends the functionality or analytical capabilities of the shared system. The project guidance is intended for a mixed cohort that may include Data Science, Computer Science and Business Analytics students. The assessment is divided into two main components: Proposal and Implementation. The Proposal accounts for 40% of the assessment, while Implementation accounts for 60%. Both the group trunk and individual trunk contribute to the assessment. The group proposal requires students to describe what the group intends to build, explain the problem being addressed, outline the proposed approach and identify the main functions and responsibilities within the project. Students should demonstrate a clear understanding of the project objectives and provide an appropriate plan for developing the shared system. The implementation stage requires students to develop the common group functionality and then complete their individual refinement. The shared component provides the basic project framework, while the individual refinement allows each student to investigate a specific aspect of the problem and add specialised functionality. Depending on the selected project topic, individual refinements may involve data analysis, visualisation, optimisation, prediction, monitoring, reporting or other computational features. The project topics include practical applications such as productivity and task-management systems, supermarket sales analysis and other data-driven applications. Students are expected to use Python and appropriate libraries or computational techniques to implement their solutions. The project materials provide examples involving data structures, CSV files, functions, numerical calculations, visualisation and analytical dashboards. The assessment emphasises both technical implementation and the student's ability to explain the problem, approach and functionality of the developed system. Students should demonstrate appropriate use of programming concepts, mathematical foundations, algorithms and data-analysis techniques. The individual refinement should clearly extend the common project and demonstrate the student's own contribution to the overall solution. Overall, the assessment develops practical digital-technology skills through collaborative project development followed by individual technical refinement. It provides experience in project planning, programming, computational problem solving, data analysis, visualisation and the application of mathematical and algorithmic concepts to practical problems.

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Data Science 1,000 words

Individual Project – Image Segmentation

This individual project focuses on image segmentation using a subset of the ADE20K dataset. The assessment requires students to investigate viable image segmentation models, analyse and visualise the provided data, develop appropriate data preprocessing procedures, train a segmentation model and critically evaluate the resulting performance. The assignment is worth 25% of the module assessment and is designed to assess students’ ability to apply research methods to a data science problem, communicate analytical findings effectively and select appropriate methods while understanding their advantages and limitations. Students are required to work with the provided ADE20K dataset and produce a model capable of semantic segmentation for four specified object classes: person, car, book and airplane. The model must identify which regions of an unlabelled image correspond to these four classes. The assignment specifically requires semantic segmentation rather than simply identifying whether an object is present. Treating the task as binary segmentation, where all objects are considered a single foreground class, will result in a significant penalty. The project requires students to investigate different approaches and models, perform exploratory data analysis, develop suitable preprocessing procedures and customise their selected model or models to improve performance. Students may use more than one model, although at least one model must be partially or fully trained by the student. Where multiple models are used, comparison with pretrained models is encouraged. Potential approaches include segmentation architectures such as U-Net and Mask R-CNN, with appropriate model selection justified through relevant literature and experimental evidence. The report should contain at least four core sections: an Introduction incorporating a literature review, Data Description and Exploratory Data Analysis, Methodology, and Results and Discussion. The literature review should cite at least three relevant research papers. The results section should include evaluation of three test images using the developed model and comparison with relevant published literature. Students are expected to provide a critical analysis of their work rather than simply reporting numerical results, explaining the reasons for observed outcomes and considering how modelling and implementation choices affected performance. The assessment also requires a documented Google Colab notebook containing the implemented steps used to train and evaluate the model. The notebook should be accessible to markers and should demonstrate the preprocessing, model development, training and evaluation process. The report must be between 700 and 1,000 words, excluding references and code, and should include code in text format as an appendix rather than screenshots. Figures and tables should have clear captions explaining what they present and their source. Assessment criteria include literature review and context, dataset description and exploratory data analysis, implementation quality, quality of analysis and critical discussion, and report quality and structure. Strong work is expected to demonstrate appropriate model selection, effective preprocessing and augmentation, suitable evaluation metrics such as Intersection over Union (IoU) and Dice score, meaningful visualisation and a critical interpretation of results and limitations.

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2,000 words

Internationalisation and Global Expansion Plan for a Small or Medium-Sized Enterprise

This assessment is an individual report that requires students to develop a plan for taking a small or medium-sized enterprise, family firm, or new start-up into a global market. Students may create their own start-up business plan or select an existing SME or family business from any country, but the chosen organisation must be a small or medium-sized firm and must be different from the business idea submitted for Assignment 1. The report focuses on developing a practical internationalisation strategy that explains how the selected firm can enter, compete and grow in a new international market. The report begins by establishing the background of the selected firm and its contextual environment. Students should identify whether the organisation is a new start-up or an existing firm, provide relevant information about its country, explain its business type and consider operational or resource challenges. Where a start-up is selected, students should identify potential resource scarcity and explain how these challenges could be overcome. The report then introduces the firm's products or services and explains the value proposition and reasons why customers should purchase them. A feasibility analysis is required to demonstrate how the business opportunity or market gap was identified. Students must use the relevant Week 6 teaching resources to explain the feasibility of the proposed product or service and its potential within the firm's home market. The report then develops an internationalisation strategy, using the specified Week 5 and Weeks 8–10 teaching resources. This includes selecting and justifying the target international market, evaluating appropriate market entry strategies, explaining the proposed innovation, developing a new product or service for the target market and applying relevant innovation models. The internationalisation chapter also requires students to consider how the firm will manage and expand in the selected market, including the use of networks, competitors and competitive strategies. Students must develop a marketing approach for the new market, identify the target customer segment and explain how innovative promotion and advertising methods will be used. Relevant theories and frameworks, including Porter’s Five Forces, PESTEL and Embeddedness, should be applied to the selected firm and its context with suitable examples. Further sections address funding and finance, intellectual property and the wider impacts of the firm. Students must explain how the international expansion will be funded, including potential sources such as angel investors, venture capital and crowdfunding, with estimated funding amounts. The report should also explain how intellectual property will be protected in the new market and evaluate potential social, economic and community impacts. The final section is a personal reflection using Gibbs' Reflective Cycle. Students should reflect on their learning throughout the module, including relevant case studies discussed during tutorials, difficulties encountered, lessons learned and steps for improving future learning and performance. The report must use reliable sources and Harvard referencing, with relevant graphs and tables encouraged to improve clarity and presentation.

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Leading and Managing Change 2,000 words

Develop a Change Management Plan for a Specific Organisational Context

This assessment is an individual report for the BUSI1815 Leading and Managing Change module. The task requires students to develop a change management plan for a specific organisational context involving either a global organisation or a UK-based organisation. The proposed plan should be based on an actual organisational change initiative and demonstrate an understanding of the theories, concepts and tools covered throughout the module. The report requires students to analyse the selected organisational change initiative and develop a practical and theoretically informed change management plan. The analysis should consider the organisational context in which the change is taking place and examine the factors that may influence the success of the change strategy. Particular attention should be given to resistance to change and the managerial, organisational culture and social factors that can affect how change is introduced and managed. A central requirement of the assessment is the critical evaluation and application of relevant change management models and frameworks. Students should use appropriate theories and concepts to support their analysis and demonstrate how these can be applied to the selected organisation and its specific change initiative. The resulting change management plan should provide a detailed implementation strategy that explains how the proposed change can be managed within the chosen organisational context. The report should also address the management of resistance to change, particularly where the organisation operates in a global context. Students are expected to consider how managerial practices, organisational culture and social factors may create challenges or opportunities during the change process. The plan should therefore connect theoretical perspectives with practical organisational considerations and provide appropriate strategies for implementing and managing the change. The assessment has a total word length of 2,000 words and is weighted at 60% of the module assessment. The required structure consists of an Introduction of approximately 200–300 words, a main Change Management Plan of approximately 1,600–1,900 words, and Recommendations and Conclusion of approximately 200–300 words, followed by a reference list. The main section should present the change management plan for the chosen company and should be supported by relevant change management theories and concepts. The assessment addresses the learning outcomes relating to analysing the effects of resistance to change in a global context and critically evaluating change management models and frameworks. Students should therefore demonstrate critical understanding, appropriate application of theory, analysis of organisational and contextual factors, and the ability to develop a practical change management plan supported by academic evidence.

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Engineering and Environment Advanced Practice London Campus Consultancy Project 2,000 words

Individual Reflective Report – Group Consultancy Project

This assessment is an individual reflective report based on the student’s learning and experience during the Group Consultancy Project for the Engineering and Environment Advanced Practice London Campus Consultancy Project module at Northumbria University. The assessment requires students to critically reflect on their activities, contributions, skills development and professional learning throughout the group-based consultancy experience. The report has a total word limit of 2,000 words, excluding the table of contents, page numbers and captions for figures and tables. It is structured around two main components: a Progress Report of approximately 1,000 words and a Reflection of Learning and Development of approximately 1,000 words. The Progress Report brings together the main themes of the module from the perspective of additional skills development, engagement in self-development, group-based learning, cultural awareness and ethical awareness. Students are expected to discuss key personal activities undertaken during the group project, skills gained through participation, personal contributions to the project, and the development of interpersonal and intrapersonal skills. Academic literature can be used to support the discussion. The Reflection of Learning and Development section requires students to critically evaluate their personal strengths and weaknesses and demonstrate their ability to engage in continuous self-development within the context of group project work. Students should reflect on a range of project activities and provide examples of their involvement in decision-making, problem-solving, communication and influencing, technical skills, collaboration, innovation and proactivity. The assessment therefore focuses not only on describing what students did, but also on evaluating what they learned and how the experience contributed to their professional and personal development. The assessment is worth 50% of the total marks available for the module, which is assessed on a pass/fail basis. The assessment rubric evaluates the Progress Report at 50%, Reflection of Learning and Development at 40%, and Writing Style at 10%. Strong submissions are expected to provide clear and relevant examples, integrate activities with skills and contributions, demonstrate critical reflection on strengths and weaknesses, and present a well-structured and professional written report. Students are also expected to follow the university’s requirements regarding academic integrity and the responsible use of generative AI. The assessment guidance states that AI may assist with activities such as improving grammar, formatting structure, organising ideas and generating suggestions, but the main content, analysis and conclusions must remain the student’s own work. Students are required to declare their use of AI tools when submitting the assessment.

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Engineering and Environment Advanced Practice London Campus Consultancy Project 5,000 words

Group Consultancy Report – Engineering and Environment Advanced Practice

This assessment is a group consultancy project for the LD7119 Engineering and Environment Advanced Practice London Campus Consultancy Project module at Northumbria University. Students work in consultancy groups of four to five members and are assigned a live project in collaboration with an organisation and the university. The purpose of the assessment is to investigate an organisational issue or requirement and develop practical, evidence-based solutions that can support the organisation in implementing improvements. The main assessment consists of a 5,000-word Group Consultancy Report and a compulsory 10-minute client presentation. The report is expected to demonstrate a professional and commercially appropriate approach to consultancy work. It should provide a clear introduction to the project, establish the organisational context, and analyse the business requirements and needs of the client organisation. The report should then explain the research methodology used, including appropriate ethical considerations and the design of the practical work undertaken. A substantial part of the assessment focuses on research, discussion and findings. Students are expected to collect and analyse relevant evidence, present their findings clearly, and provide evidence of practical implementation and testing where applicable. The assessment therefore requires students to connect academic research and relevant theories with practical consultancy activities and organisational requirements. Evidence from diagnostic tools, feedback and other appropriate sources can be incorporated into the report to support the analysis and conclusions. The final part of the report focuses on recommendations and improvements. Students should develop practical and actionable recommendations that are relevant to the organisation and can contribute to the successful implementation of the proposed ideas. Recommendations should be supported by the research findings and should demonstrate an understanding of the organisation's requirements and potential implementation considerations. The assessment is worth 50% of the total marks available for the module, which is assessed on a pass/fail basis. The report has a 5,000-word limit, excluding the table of contents, page numbers and captions for figures and tables. The client presentation is compulsory, although it does not have marks directly allocated to it; its purpose is to help the client and supervisor understand the consultancy project. The assessment is evaluated across professional and commercial presentation and introduction, business and requirement analysis, research methodology including ethics and practical work design, research and findings including implementation and testing, and recommendations including improvements. Students are also required to acknowledge sources appropriately and complete the assessment declaration regarding their work and any use of generative AI. The assessment brief states that AI may assist with activities such as improving grammar, structure, organising ideas and providing suggestions, but the main content, analysis and conclusions must remain the student's own work.

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Cloud and Big Data Technologies 2,500 words

Cloud and Big Data Technologies – Summative Assessment: Cloud and Big Data Security Application

This summative assessment for the CST4067 Cloud and Big Data Technologies module requires students to design, implement and evaluate an individual cloud and big data security application. The assessment focuses on applying techniques for the complex transformation and processing of data within distributed and cloud-based environments, while considering security, privacy and access-control requirements. Students are expected to develop a practical application and document its design, implementation and evaluation through a technical report and a short demonstration video. Students are given flexibility to select their own project idea, provided that the proposed application is appropriately scoped for the available development period and demonstrates relevant cloud, big data and security technologies. Suggested project areas include data science applications using SQL, MongoDB and cloud storage, privacy-preserving data processing such as Differential Privacy, multi-party authentication, group-based security and access control, Multi-Level Security, Attribute-Based Encryption, and distributed or cloud-based applications incorporating security protocols such as SSH, SSL or IPSEC and access-control mechanisms such as RBAC. The Design and Implementation Document should be no longer than 2,500 words and should explain the major design and implementation aspects of the project. Expected content includes an introduction covering the aims, objectives, project concept, security concepts and cloud technologies used; a requirements specification addressing programme behaviour and security requirements; analysis and design covering protocols, access control and interaction, sequence diagrams or process specifications; implementation details explaining what was achieved and how it was developed; and an evaluation and conclusion discussing successful and unsuccessful aspects, problems encountered and lessons learned. Relevant references, including tutorials, books and academic articles, should also be provided using Harvard or IEEE referencing. The assessment also requires students to submit the implemented Cloud and Big Data Security application together with a highlight demonstration video. The video must be no longer than seven minutes and should demonstrate the main features of the application, including relevant interactions, implementation highlights, security features and, where appropriate, attack scenarios. Assessment is based on the Design and Implementation Document, originality, advanced features, and the effort and quality demonstrated in the application. The assessment specification places particular importance on original development, clear documentation of any tutorials or existing resources used, and evidence that the student understands the technologies implemented. Suggested technologies and project ideas include Google Cloud, Hadoop, Spark, cloud storage, data pipelines, security protocols, access control and privacy-preserving techniques.

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Databases 1,000 words

Assessment #1 – Advanced Databases: NORTHERNTOURS Database Design and Implementation

This assessment for the Advanced Databases module (KL7011) focuses on the analysis, design and implementation of a database system based on the NORTHERNTOURS scenario, a fictitious transport company operating a fleet of luxury coaches across cities, towns and tourist locations in Northern England. The assessment requires students to demonstrate advanced database knowledge through conceptual modelling, logical database design, SQL implementation, data manipulation and the evaluation of alternative database technologies. The assessment addresses learning outcomes relating to the data life cycle, advanced data modelling and database design, as well as professional, legal, ethical, security, sustainability and risk considerations. The first part requires students to develop a conceptual database design for NORTHERNTOURS using Entity-Relationship (ER) or Enhanced Entity-Relationship (EER) modelling. The design should identify relevant entities, relationships, key attributes, primary keys and structural constraints. Students then convert the conceptual model into a logical relational schema using ER/EER-to-relational mapping, identify primary and foreign keys, ensure the relations satisfy Third Normal Form (3NF), select and justify a consistent naming convention, and produce a textual data dictionary containing relevant names, descriptions and constraints. The logical design is subsequently implemented using Oracle 11g, 12c or higher through appropriate SQL DDL statements and database constraints. The second part involves populating selected database relations with self-generated sample data and demonstrating database retrieval capabilities. Students must provide SQL DML statements, relational algebra expressions and SQL queries for specified NORTHERNTOURS business requirements. The solutions must be executed in a live Oracle environment and supported with appropriate output evidence. The third part extends the database analysis by considering object-relational and NoSQL database technologies. Students evaluate which aspects of the NORTHERNTOURS conceptual design could benefit from object-relational implementation, develop and populate a suitable object-relational subset, and demonstrate it through complex queries. They also analyse where NoSQL concepts could provide benefits and discuss design choices supported by representative NoSQL implementation code. Finally, students prepare a concise report for the NORTHERNTOURS managing director addressing sustainability, professional, legal, ethical and security issues, together with diversity, inclusion, cultural, societal and environmental considerations and commercial risk management. The report should use a critical review of relevant literature, systems, developments and standards and follow Harvard referencing conventions.

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Business 800 words

Individual Reflection on Group Research Presentation

This assignment is an individual written reflection based on a group research presentation completed for the Principles of International Business module. The assessment requires students to reflect on both the research topic explored by their group and the process of working collaboratively to develop and deliver the group presentation. The reflection has a word count of 800 words and should demonstrate thoughtful consideration of the student's individual experience, contribution and learning. The first part of the reflection introduces the research topic investigated by the group. Students are expected to provide a concise summary of the subject explored and establish the context for their reflection. This provides an opportunity to explain the focus of the group's research and the main area investigated. The second area focuses on the group project experience. Students should reflect on their own contribution to the group presentation and evaluate how effectively the group collaborated. The reflection should consider aspects of teamwork such as communication, presentation, time management and conflict resolution. Students should also discuss what they learned from undertaking the research project, including critical reading and thinking, development of the research topic, data collection and analysis, and the process of making recommendations. Importantly, the reflection should include at least one specific example of how a problem was identified and resolved during the group process. The final area focuses on research skills development. Students should identify the research skills they developed while conducting the chosen research topic and provide examples of how these skills were applied during the group research project. They should also discuss challenges encountered while completing the project and explain how they addressed or overcame those challenges. Overall, the assignment is designed to encourage students to critically reflect on their group research and presentation experience, rather than simply describe what happened. It provides an opportunity to consider individual contributions, teamwork, research capabilities, problem-solving and personal learning gained through the project. The assessment therefore combines reflection on the international business research topic with evaluation of collaborative working and the development of research skills.

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Business 850 words

HopeLink Community Support and Food Security Database

This assignment requires students to design, develop and analyse a relational database for HopeLink Community Support and Food Security, a fictitious non-profit organisation working across rural and urban communities to reduce poverty and hunger. HopeLink currently relies on spreadsheets, which have resulted in inefficiencies and reporting errors. The proposed database is intended to improve operational efficiency, transparency and evidence-based reporting while supporting the organisation's work towards United Nations Sustainable Development Goals (SDGs) 1 and 2: No Poverty and Zero Hunger. The database development project involves five main entities: Beneficiary, Donor, Product, Collection and Collection Detail. Students are required to create a data dictionary defining the tables, attributes and appropriate validation rules. They must then use SQL within Microsoft Access to create the required tables through SQL View, rather than using the Access front end. Primary keys and foreign keys must be identified and implemented as part of the database design. Students must also establish relationships between the database entities and enforce referential integrity to maintain accurate information for management reporting and decision-making. Appropriate validation rules, user-friendly error messages, drop-down lists and input masks should be implemented where required. The database must be populated with sufficient realistic data for testing, with minimum requirements of 10 Beneficiary records, 10 Donor records, 20 Product records, 10 Collection records and 20 Collection Detail records. A further component requires students to develop five useful SQL queries in Microsoft Access to support analysis and reporting for HopeLink. The queries must follow specific requirements, including one parameter query, at least three queries containing a WHERE clause, at least one aggregate query and at least two queries involving joins across more than two tables. Students must provide screenshots of the SQL code and resulting outputs, together with an English explanation and a short justification of how each query could support HopeLink's operations and decision-making. The final component is an 850-word maximum business insights report investigating the use of food banks in the UK and considering how initiatives could support SDG 1 and SDG 2. Students are expected to use reliable external data, present relevant graphs and analyse current trends in food-bank usage. This section requires Harvard referencing and should use reliable academic, industry and other appropriate sources. The report is based on SDG 1 and SDG 2 and is not directly linked to the database developed for the assignment. Overall, the assignment assesses students' ability to apply data-modelling techniques, database design principles, SQL and data analytics to support organisational operations and strategic decision-making. It combines practical database development in Microsoft Access with data analysis and a business-focused evaluation of food-bank trends and sustainability goals.

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Managing Customer Experience 1,000 words

Managing Customer Experience – Customer Experience Strategy Report

This assessment for the Managing Customer Experience module requires students to prepare a 1,000-word business report evaluating the customer experience (CX) strategy of one selected banking organisation. Students must choose one company from the organisations provided in the assessment brief and analyse its customer experience strategy within the specific country in which it operates. The report is designed to develop a critical understanding of the importance of customer experience for business success and the ways in which organisations can create a seamless omnichannel customer journey. The assessment provides a choice of six banking organisations: Lloyds Banking Group in the United Kingdom, HDFC Bank in India, Habib Bank Limited (HBL) in Pakistan, Nabil Bank Ltd in Nepal, Prime Bank PLC in Bangladesh, and Access Holdings/Access Bank in Nigeria. Students are required to clearly identify the selected organisation and country in their report and use relevant customer experience concepts, academic literature, research and practical examples to support their analysis. The first major requirement is to explain the concept of customer experience and critically review its importance to the success of the selected banking brand. The report should consider the role of CX, the mutual benefits created for the organisation and its customers, and the impact of customer experience on business performance, including financial performance. Students should also provide specific examples demonstrating how the selected bank has used customer experience to create or strengthen competitive advantage. The second major requirement is to evaluate how the selected bank delivers a seamless omnichannel customer experience. This requires discussion of the organisation's approach to creating a consistent customer journey across relevant channels. Students must develop a detailed customer persona based on research and data analysis, covering the persona's profile, goals, pain points and motivations. They must also create a customer journey map using the recommended class template. The journey map should identify stages, needs, activities, feelings, pain points and opportunities for improvement. The report should evaluate the effectiveness of the selected bank's customer journey and identify areas where the organisation could improve the ease and quality of the customer's experience. The customer persona and customer journey map are important components of the assessment, and the words contained within these visual templates do not count towards the 1,000-word limit. The report must be written in an academic style and in the third person. Harvard referencing is required for academic sources, figures, diagrams and independent research. The main report has a maximum word count of 1,000 words, excluding the cover sheet, title page, table of contents, references and appendices. The assessment therefore combines academic research, customer experience theory, organisational analysis, customer persona development, journey mapping and critical evaluation of omnichannel customer experience.

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Leading Through Digital Change 1,000 words

Leading Through Digital Change – Digital Transformation Report

This formative assessment for the Leading Through Digital Change module requires students to act as a Digital Transformation Specialist and prepare a Digital Transformation Report for a selected retail organisation. The assessment focuses on how traditional brick-and-mortar retailers can respond to the rapid growth of e-commerce and changing customer expectations. Students are required to evaluate the digital changes affecting their selected organisation and propose appropriate strategic changes that can help maintain competitiveness and create business value. The assessment is aligned with Learning Outcome 1, which focuses on applying knowledge and understanding of management and leadership strategies in organisations experiencing digital change. Students must select one organisation from the options provided in the assessment brief. The available organisations are River Island, Khaadi, Shoprite Holdings Ltd, Reliance Retail and Carphone Warehouse. Each organisation operates within the retail sector but has different markets, products and business contexts, allowing students to investigate digital transformation from an organisational perspective. The main task requires students to critically review and propose an appropriate digital transformation strategic framework that the selected organisation should employ in response to current digital change. Students must use one digital transformation framework from the specified choices: McKinsey 4Ds, BCG 3 Stages, Gartner's 6 Steps or Cognizant's 4 Pillars. The chosen framework should be applied to the organisation rather than simply described. The report should also establish digital transformation objectives that support important organisational departments, particularly operations, ICT and marketing. Examples may be used to strengthen the discussion, while higher-level work should demonstrate extensive personal research and critical evaluation. The report should demonstrate an understanding of the organisation's technological challenges, factors driving digital transformation, internal and external threats, opportunities and emerging digital practices. Stronger submissions are expected to provide clear justification for the selected transformation framework and explain how proposed objectives connect with the factors driving the organisation's digital transformation. The marking criteria place importance on knowledge, analysis, justification, evidence-based discussion and the use of relevant and recent research. The submission has a maximum main-body word count of 1,000 words. The cover page, table of contents, list of abbreviations, references and appendices are excluded from the word count. The required structure includes the BPP cover sheet, table of contents, list of abbreviations where appropriate, introduction, Task 1, conclusion, references and appendix if required. The report must be written in the third person, use professional academic formatting, include correctly labelled tables and figures where applicable, and use Harvard referencing and in-text citations. Overall, the assessment develops students' ability to analyse digital transformation challenges in retail organisations and apply management and leadership concepts to develop a strategically justified response to digital change. It combines organisational analysis, digital transformation frameworks, strategic objectives, academic research and professional business-report writing.

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800 words

Individual Reflection on Group Research Presentation and Research Skills Development

This assessment is an individual 800-word reflective piece that requires students to reflect on their experience of completing a group research project and delivering a group presentation. The reflection focuses on the research topic explored by the group, the student's individual contribution to the presentation, the effectiveness of group collaboration, the development of research skills and the challenges encountered throughout the research process. The reflection begins with an introduction to the research topic investigated by the group. Students are expected to provide a concise summary of the topic explored and establish the context for their subsequent reflection. The discussion should demonstrate an understanding of the research undertaken by the group and provide a clear foundation for evaluating the student's experience. The second area focuses on the group project experience. Students should describe their individual contributions to the group presentation and critically reflect on how effectively the group worked together. The reflection should consider aspects of teamwork such as communication, presentation skills, time management and conflict resolution. Students should also identify what they learned from both the teamwork process and the research project, including areas such as critical reading and thinking, research topic development, data collection and analysis, and making recommendations. At least one specific example of how a problem was resolved during the group process must be included to demonstrate practical reflection on the team's experience. The third area focuses on research skills development. Students should identify the research skills they developed while conducting the chosen research topic and provide specific examples of how these skills were applied during the group research project. The reflection should also discuss challenges experienced while completing the research and explain how those challenges were addressed or overcome. Overall, the assessment requires students to move beyond simply describing what happened and provide meaningful reflection on their learning and development. The reflection should demonstrate how participation in the group research project contributed to the development of teamwork, communication, research, analytical and problem-solving skills. It should also consider how these skills can support future academic and professional activities. The assessment is marked using four criteria: presentation and structure of the reflection, breadth and depth of reflection, research skills development, and group presentation experience. The rubric allocates 10 points to presentation and structure, 30 points to breadth and depth of reflection, 40 points to research skills development and 20 points to group presentation experience, for a total of 100 points. The assessment instructions also state that students must not use AI tools for the assignment.

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Operations and Supply Chain Management 2,000 words

Operations and Supply Chain Management – Individual Reflective Report

This assessment is an individual 2,000-word reflective report for the Operations and Supply Chain Management module at De Montfort University. The report requires students to reflect critically on their experience of completing Assessment One and to demonstrate how their learning developed throughout the project. The assessment focuses on reflective practice, application of relevant theories, critical analysis of team and project experiences, and the development of an action plan for future professional practice. The report begins with an introduction explaining why reflection on practice is important and connecting reflective practice to relevant learning theories where appropriate. Students are required to identify the particular areas they will focus on within the report and explain why these areas are important and interesting to explore. This section establishes the purpose and scope of the reflection and provides a foundation for the critical discussion that follows. The main body should use appropriate sub-headings to organise the discussion into different areas. Students should explain how the team collectively established specific approaches relating to the topics selected in Assessment One. The report should then examine how the approach changed as the project progressed and connect these changes to relevant theories. Both successful and unsuccessful aspects of the project should be critically considered, rather than simply describing what happened. Detailed examples from the situation analysis and problem-solving components of Assessment One should be used to support the arguments and demonstrate meaningful reflection. The report should demonstrate critical understanding of operations and supply chain management issues, including the ability to critically appraise and adapt to tangible, intangible and information-related aspects of the global supply chain. It should also reflect on capacity planning and process design decisions relating to the production of goods and services. The emphasis is on connecting practical project experience with relevant academic concepts and theories. The conclusion should identify the key learning points gained from the project process and the consultancy presentation. Students should reflect on how these experiences have contributed to their knowledge, skills and professional development. The final part of the report should present a clear action plan explaining how the learning gained from the project will be taken forward into the student's future career. The assessment is worth 30% of the module and has a required length of 2,000 words, with an accepted range of 1,800–2,200 words. Assessment criteria include introduction and rationale, application of theory and concepts, critical analysis and evaluation, conclusion and action plan, and academic skills including Harvard referencing, source quality and quantity, structure and presentation.

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Leadership in a Digital Age 5,000 words

Advanced Practice Research Project – Reflective Individual Report and Poster Presentation

This assessment requires students to produce a 5,000-word individual business consultancy report based on a chosen organisation. The selected organisation may be a private company, a public organisation that is not government owned, or a non-governmental organisation. The chosen organisation acts as the client and the student takes the role of a consultant who investigates a current or potential business challenge, examines the resulting issues and develops recommendations that can provide strategic value to the organisation and its wider industry. The project requires students to formulate a business project that has strategic importance within a chosen area of management. The report should identify a specific organisational challenge and the issues resulting from that challenge, supported by recent evidence demonstrating that the challenge is ongoing, unresolved or likely to become significant in the future. The challenge should be connected to current affairs and emerging trends within the relevant industry and business environment. The report should also provide a consultant's perspective on why the challenge matters to the selected organisation. A clear purpose for the report must be established. This should explain why the selected challenge and issues are being investigated, how the research will benefit the client organisation and how the project relates to the chosen organisational specialisation area. The report should demonstrate an understanding of the importance of strategy in business and establish a clear connection between the identified problem, the research undertaken and the proposed solutions. Stakeholder analysis is a major component of the assessment. Students must identify relevant internal and external stakeholders, explain their relationship with the identified challenge and issues, and evaluate the impact of the research on these stakeholder groups. The analysis should consider stakeholder power and interest and demonstrate how the proposed project and its findings could affect different stakeholders. The main analytical section requires the use of secondary data, including both conceptual and numerical evidence. Students should critically evaluate relevant information using appropriate management frameworks and analytical approaches. The evidence should be used to investigate the challenge, understand its causes and consequences, and support the development of appropriate recommendations. The report should demonstrate critical thinking rather than simply describing information. The final section provides recommendations designed to resolve the identified challenge and resulting issues. Recommendations should be directly supported by the secondary-data analysis and critical evaluation and should be relevant and realistic for the selected organisation. The conclusion should return to the central challenge and explain how the purpose of the report has been addressed, while demonstrating the strategic value of the recommendations for the organisation and, where appropriate, the wider industry. The recommended structure consists of a declaration page, title page, contents, executive summary, introduction, challenge and issues, purpose of the report, stakeholder analysis, evaluation and analysis of secondary data, recommendations and conclusion, Harvard references and appendices where required. The suggested allocation is approximately 500 words for the executive summary, 300 for the introduction, 500 for the challenge and issues, 200 for the purpose, 600 for stakeholder impact, 2,000 for secondary-data evaluation and 900 for recommendations and conclusion. The total report length is 5,000 words, excluding the front cover, contents, bibliography and appendices.

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Global Business Strategy 2,500 words

Global Business Strategy: Strategic Analysis and Growth of a Global Company

This Global Business Strategy assessment is an individual e-portfolio that requires students to conduct a comprehensive strategic analysis of a selected global company facing a significant business challenge. The assessment focuses on the identification and analysis of a real organisational problem, evaluation of the global business environment, development of sustainable strategic options, the role of strategic leadership, and recommendations for future growth and competitiveness. Students are required to select a global company from any industry and investigate challenges such as loss of market position, difficulties in gaining or regaining market share, operational challenges, or declining revenues and profits. Relevant strategic theories, models and academic evidence should be used throughout the analysis. The first stage focuses on selecting the organisation, identifying its strategic purpose, vision, mission and objectives, and analysing the significant problem affecting the company. Students are expected to investigate both internal and external aspects of the global business environment and identify factors that may have contributed to the organisation's challenges. Appropriate theories and strategic models should be applied to provide a critical analysis of the business context. The second stage examines sustainable business strategies, diversification and competitive advantage. Students are required to conduct a resource audit and use an appropriate strategic model to assess how the organisation can sustain competitive advantage. The assessment also requires students to propose an appropriate mode and strategy for entering an international market in which the selected company does not currently operate, supported by relevant theories and models. The third stage addresses strategic change, leadership and governance. Students must demonstrate an understanding of effective leadership styles and their relevance to strategic change, good governance and ethical business practices. The role of ethics in international business should be examined using relevant practical examples and evidence. The fourth stage focuses on good strategy execution, evaluation, recommendations and conclusion. Students are expected to justify how the selected organisation can execute strategy effectively using available resources and process management tools that support continuous improvement. At least two strategic options should be considered, with attention given to their feasibility, potential impact, alignment with organisational goals and available resources, as well as the role of leadership and leadership styles. The assessment concludes with a summary report of approximately 1,000–1,500 words, synthesising the key learning and insights gained from the individual tasks. The overall report should be approximately 2,500 words, excluding references and appendices, and should follow the ULBS Harvard referencing style. Evidence and artefacts may include business-journal articles, professional or government reports, relevant videos, analytical tables, competitive-position graphs and financial or balanced-scorecard information. The completed e-portfolio is compiled in PebblePad and submitted as a PDF through Turnitin.

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Leadership in a Digital Age 4,000 words

Leadership in a Digital Age: Leadership Strengths and Development Needs

This individual assessment for the Leadership in a Digital Age module requires students to produce a 4,000-word report that critically analyses their leadership strengths and development needs within the context of the digital age. The assessment places particular emphasis on critical reflection, self-awareness, contemporary leadership theory and continuous professional development. Students are expected to apply relevant leadership models and frameworks, use evidence from diagnostic assessments and connect their personal development to the skills and behaviours required of effective digital leaders. The report is structured into five main sections. The first section critically reviews contemporary leadership models and theories in relation to digital leadership. Students are expected to select two or three relevant leadership theories, explain their key principles and critically evaluate their relevance to digital leadership traits and characteristics. The assessment encourages the selection of contemporary approaches rather than outdated leadership theories and requires students to demonstrate clear links between theory and the demands of leading in digitally changing environments. The second section focuses on self-analysis. Students identify relevant digital leadership traits and conduct a thorough evaluation of their own leadership characteristics using a range of diagnostic tools. The assessment identifies tools covering temperament, workplace culture, motivation at work, emotional control and management skills, together with other available university diagnostic assessments. Students should report and interpret their results and use the findings to develop a personal SWOT analysis focused specifically on digital leadership strengths and areas requiring development. The third section examines leadership capabilities and behaviours when leading a hybrid, multi-generation team. Students should consider themselves working as a digital leader responsible for such a team, identify potential challenges and propose appropriate solutions. The discussion should evaluate how leadership capabilities and behaviours can be applied in practice or within a future role. Particular attention must be given to the ethical, social and legal responsibilities of digital leaders towards team members. The fourth section critically evaluates how artificial intelligence can support digital leadership and accelerate organisational digital transformation. Students should use a workplace example to demonstrate how emerging technologies such as machine learning, predictive analytics, intelligent automation or generative AI could improve operations, decision-making or innovation. The analysis should consider organisational benefits as well as the resources required to implement and sustain AI-driven transformation, including data infrastructure, skills and partnerships. The final section requires a Personal Development Plan based on the findings from the earlier analysis. Students should identify personal development objectives that demonstrate their ability to develop the competencies required of an effective digital leader. The plan should establish future leadership goals, learning activities, measurable success criteria and realistic timescales. Overall, the assessment requires students to integrate leadership theory, self-awareness, digital transformation, AI, team management and continuous professional development into a coherent critical analysis of their leadership development.

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Financial Mathematics

Financial Mathematics: Portfolio Analysis, Risk and Volatility Modelling

This Financial Mathematics coursework focuses on the quantitative analysis of financial assets, portfolio construction, investment risk and volatility modelling. Students are required to work with historical daily share-price data for five stocks previously selected in their portfolio. The data should cover a sufficiently long period, with at least one year of observations, and should provide positive average returns. Students must briefly describe each selected company and the nature of its business before conducting the financial analysis. The first part of the coursework requires students to calculate the expected return and volatility of each of the five companies and analyse the correlations between their asset returns. These calculations provide the foundation for evaluating the risk and return characteristics of the individual assets and their potential contribution to a diversified portfolio. The second part focuses on portfolio optimisation. Students must use an appropriate Solver function to determine portfolio risk and the percentage investment allocated to each asset for a selected target return. The process must be repeated for different target returns to generate an efficient frontier curve. This analysis demonstrates the relationship between expected portfolio returns and the associated levels of portfolio risk. The third part requires students to calculate Sharpe ratios for a range of expected portfolio returns and volatilities obtained through the portfolio analysis. Using a risk-free investment with a guaranteed return of 1.5%, students must determine the equation of the Capital Market Line and discuss its economic significance in relation to investment decisions and portfolio performance. The fourth part applies linear regression analysis to calculate the beta of each asset in the portfolio and discuss the significance of beta as a measure of systematic risk. Students must also estimate the portfolio's Value at Risk at the 5% level and discuss the contribution of each individual asset to the estimated portfolio VaR. The fifth part focuses on financial volatility modelling using R. Students must estimate the volatility of a selected individual asset using ARCH/GARCH models and their extensions, identify the most appropriate model and provide an explanation supporting the model selection. Finally, students must present their findings in non-technical language suitable for a potential investor. The conclusion should identify the implications of the analysis for selecting an efficient portfolio and discuss other relevant performance measurements. The coursework requires clear explanations of the methods and formulae used in Excel worksheets and R outputs, while unnecessary explanations of portfolio theory and the Capital Asset Pricing Model should be avoided.

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Business Simulation – Cyber Security 2,500 words

L7 Business Simulation – Cyber Security: Ethical Hacking and Vulnerability Assessment

This assessment is an individual cybersecurity portfolio based on a simulated business environment involving a fictional client, VulnTech Inc. Students take the role of a junior cybersecurity analyst and investigate vulnerabilities within a server deployed for the organisation’s legacy systems. The practical activities use the TryHackMe platform to simulate the web server environment and require students to apply ethical hacking techniques within an authorised scenario. The assessment focuses on the first three phases of ethical hacking: footprinting, scanning and enumeration, and gaining access. Students are required to gather information about the VulnTech server, including relevant details about its domain, IP range, network infrastructure, operating system, name servers, open ports and other technical information. They must provide evidence of the tools used, justify their selection, critically evaluate the methodology adopted and recommend appropriate mitigation strategies. The second task involves scanning and enumerating the server using information obtained during the footprinting stage. Students must identify potential vulnerabilities and provide evidence of the tools and methods used. The assessment requires students to critically evaluate their available options, explain the reasoning behind their decisions and recommend suitable strategies for mitigating identified risks. The third task requires students to gain access to the VulnTech server by exploiting one of the vulnerabilities identified during scanning and enumeration. Evidence of the tools and methodology must be provided, together with a critical evaluation of the approach, justification of decisions and recommendations for addressing the identified vulnerabilities. Students must also provide evidence of completing at least four different TryHackMe rooms or modules undertaken during the semester. The final component is a 1,500-word summary report reflecting on the key insights gained throughout the tasks. This report should consolidate the student's learning, discuss the main challenges and vulnerabilities identified, evaluate mitigation recommendations and critically examine the legal and ethical considerations associated with cybersecurity and ethical hacking practices. The assessment is designed to develop students' ability to analyse business and cybersecurity environments, identify organisational issues, evaluate alternative approaches, make informed management decisions and justify resource allocation. It also requires consideration of Environmental, Social and Governance (ESG) implications and the potential effect of cybersecurity practices on organisational perception and performance. The portfolio uses Harvard referencing, with appropriate academic and external sources cited throughout.

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Business Project 5,000 words

Business Consultancy Project: Strategic Analysis of a Business Challenge

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Applied Modelling and Visualisation 2,500 words

Applied Modelling and Visualisation – Hexawing Airways Passenger Satisfaction Analysis

This assessment is a 2,500-word consultancy report for the Applied Modelling and Visualisation module within the MSc Management with Data Analytics programme at BPP University. The assignment requires students to work as Data Analytics Consultants for the fictional Hexawing Airways and analyse a passenger satisfaction dataset containing more than 103,000 records from the airline's database. The purpose of the assessment is to apply machine learning, data analysis and visualisation techniques to identify factors that influence passenger satisfaction and communicate meaningful findings to a varied corporate audience, including the Chief Executive Officer, senior flight personnel and cabin crew. The dataset contains a range of passenger and flight-related features, including gender, satisfaction status, age, age band, type of travel, travel class, flight distance, destination, continent and ratings for services such as inflight Wi-Fi, online booking, gate location, food and drink, online boarding, seat comfort, inflight entertainment, onboard service, leg room, baggage handling, check-in service, inflight service and cleanliness. It also includes departure and arrival delay information. These variables provide the basis for exploratory analysis, predictive modelling and visual communication of passenger satisfaction patterns. The assessment requires the development of a data-driven solution using Python and relevant Python libraries. Students must follow an established analytical methodology such as PPDAC or CRISP-DM and demonstrate an Extract, Transform and Load process, data preparation, exploratory data analysis and appropriate visualisations. Two analytical models must be selected, trained and tested to predict passenger satisfaction. The available modelling approaches include Logistic Regression, Naive Bayes, Decision Tree, Bagging, Random Forest, AdaBoost, XGBoost, Artificial Neural Networks or another appropriate state-of-the-art algorithm. The second task requires critical analysis of the two selected models, including their strengths and limitations, an explanation of the chosen loss function, discussion of accuracy metrics and a comparison table of model performance. The third task focuses on communicating findings through data visualisation, including outputs such as correlation matrices, heat maps and confusion matrices. The analysis should explain how exploratory data analysis guided model selection and how visualisation techniques communicate insights effectively. The final report should demonstrate the ability to formulate data-driven solutions, critically evaluate analytical models and appraise data visualisation techniques. The assessment also requires independent research, appropriate academic referencing and supporting evidence from the analytical process. A pre-run Python notebook must be embedded in the MS Word submission or provided through an appropriate shared link.

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Big Data and Cloud Computing 2,500 words

Big Data and Cloud Computing: FieldVision Cloud-Based Big Data Solution for AgroNova

This assessment is a 2,500-word individual report for the Big Data and Cloud Computing module within the MSc Management with Data Analytics programme at BPP University. The report is based on a fictional agricultural technology company, AgroNova, and its FieldVision project. AgroNova provides climate change and crop monitoring services to farmers in the UK and intends to expand internationally. However, its existing ageing infrastructure and manual processes present challenges to international expansion and the development of data-driven decision-making. The FieldVision project aims to use Internet of Things (IoT) technology and cloud-based big data solutions to collect, store and analyse real-time information from agricultural environments. The report requires students to act as a big data and cloud solution consultant and provide recommendations to senior management at AgroNova. The project involves IoT devices such as CropCam aerial cameras supplied by HydroSense and SmartHarvester solar-powered sensors supplied by SoilTech. These technologies collect information including crop imagery, soil moisture, temperature and humidity. The resulting data can support crop monitoring, risk assessment, early warning alerts, irrigation decisions, crop-failure claims validation and other farming-related insights. The first task focuses on Big Data Requirements and Storage Solutions. Students must identify the requirements arising from the scenario and critically evaluate a range of cloud-based big data storage solutions. The evaluation should consider factors such as capacity, functionality and costs. The second task requires students to propose one appropriate cloud-based solution architecture supported by an architecture diagram showing the essential components from data sources through to reporting. The selected architecture must be analysed in relation to AgroNova's requirements and the storage solutions considered in Task 1. The third task addresses Project Risks and Issues. Students must critically appraise the risks and issues associated with deploying the proposed cloud-based big data solution and identify appropriate mitigation approaches. These issues should be connected directly to the storage solutions and proposed architecture. The scenario highlights concerns from AgroNova's CISO, CFO and Chief Reputation Officer regarding potential data breaches, high costs and poor returns on investment, making security, financial viability and organisational risk important considerations. The report should contain an approximately 200-word introduction, an 800-word analysis of Big Data Requirements and Storage Solutions, a 500-word Proposed System Architecture section supported by relevant diagrams, an 800-word Project Risks and Issues section, and an approximately 200-word conclusion. Harvard referencing, academic research and appropriate supporting appendices are also required. The assessment addresses three learning outcomes: designing an architecture that supports complex data collection, critically evaluating data storage solutions from an enterprise systems perspective, and critically appraising issues involved in enterprise-system deployment.

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Principles of Management 5,000 words

Critical Analysis of Management Practices at Apple Inc.

This assessment is a 5,000-word individual management report examining the management theories, concepts, practices and functions of Apple Inc. The report is written from the perspective of a business consultant and is intended to provide senior management with a critical evaluation of Apple's current management practices and recommendations for changes that could improve organisational success. The assessment integrates academic management theories with the practical context of a contemporary global organisation and also requires students to reflect on their own management competencies and future career development. The first part of the report critically evaluates the management theories, concepts and practices currently used by Apple Inc. Students must explain how management contributes to Apple's success and creates organisational value, supported by appropriate academic literature, case study evidence and independent research. The assessment specifically requires consideration of the four philosophies of the Competing Values Framework and one additional relevant management theory. Students are expected to select an appropriate theory rather than attempting to apply every available management theory. The second part evaluates management as a value-adding universal activity within Apple's global business environment. Students must examine how Apple has adapted its strategies and management approaches at global, national and local levels. Frameworks such as LoNG-PEST or Porter's Five Forces may be used to analyse the external environment. The analysis should identify one global factor that creates an opportunity and one that presents a threat to Apple and explain where management can add further value. The third part critically analyses the key principles and functions of management, including planning, organising, leading and controlling. Students must identify one internal challenge faced by Apple in response to current or expected environmental changes and evaluate how management functions can be applied to address it. An appropriate academic model, such as Value Chain Analysis, VRIO or Mendelow's Matrix, should be used to justify the selected challenge and support the analysis. The fourth part focuses on critical reflection and personal skills development. Students must complete a Personal SWOT analysis, identify three career-related development objectives and prepare a Skills Development Plan covering the required competencies, resources and support, methods of achievement, measures of success and target review dates. A 500-word Reflective Statement must then critically reflect on the student's own management competencies and learning during the module. The reflection should be written in the first person and use an appropriate model such as Borton's, Kolb's, Maslow's or the GROW model, with particular attention to self-management, problem-solving and decision-making. The report should conclude by summarising the recommended changes that Apple should implement to improve its success. The main body is structured around an introduction, four assessment tasks and a conclusion, with the indicative allocation being 100 words for the introduction, 1,200 words for each task and 100 words for the conclusion. Tasks 1–3 should be written in the third person using an academic style, while Task 4 should use the first person. The submission must use Harvard referencing, appropriate academic sources, professional formatting and correctly labelled tables and figures.

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Leading Through Digital Change 1,500 words

Digital Transformation Report and Poster

This assessment requires students to act as a Senior Digital Transformation Manager and produce a Digital Transformation Report and Poster for one selected sports retail organisation. The purpose of the assessment is to evaluate the organisation's current digital environment and recommend changes that can help it maintain competitive advantage and create business value in response to continuing digital change, changing consumer expectations, e-commerce growth, sustainability requirements, digital innovation and supply chain resilience. The assessment consists of three connected sections addressing digital transformation strategy, future digital trends and digital leadership. The first section requires students to critically review and propose an appropriate digital transformation strategic framework for their selected organisation. Students must select and apply one framework from McKinsey's 4Ds, BCG's 3 Stages, Gartner's 6 Steps or Cognizant's 4 Pillars. The framework should be applied to the chosen organisation rather than simply described. The analysis should also establish digital transformation objectives that support key business functions such as operations, ICT and marketing, with relevant examples and evidence from research used to strengthen the discussion. The second section requires the design of an A4 poster evaluating two disruptive technologies or techniques that are likely to influence the smartphone industry, employment and the labour market over the next five years. Potential technologies identified in the brief include Artificial Intelligence and Machine Learning, 5G connectivity, Internet of Things, robotics, drone delivery, blockchain, augmented reality and virtual reality. The poster should communicate the expected impact of the selected technologies using academic literature and real-life examples. The third section focuses on digital leadership. Students must analyse and propose two appropriate digital leadership styles that the selected organisation should develop to effectively manage and support digital transformation. Possible approaches include hyperaware agile leadership, ethical technology leadership, people-oriented leadership, agile leadership and Goleman's leadership styles. The recommendations should be supported by relevant theories, academic literature and real organisational examples. The assessment is aligned with three learning outcomes. These address the application of management and leadership strategies during digital change, critical assessment of the impact of digital change on markets, organisations and employees, and evaluation of the leadership attributes and skills required to manage organisations and people in digitally changing environments. The final submission must include a clear introduction and conclusion, demonstrate intellectual originality and critical analysis, use appropriate academic evidence and follow Harvard referencing. The report is limited to 1,500 words, excluding the A4 poster, and students must select only one of the specified sports retail organisations for their analysis. The selected organisation should be analysed consistently across the strategic framework, future technology and digital leadership sections.

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Managing Customer Experience 2,500 words

Customer Experience Strategy: Critical Evaluation of a Global Mobile Phone Brand

This assessment requires a 2,500-word business report critically evaluating the customer experience (CX) strategy of one company operating within the global mobile phone industry. Students must select one company from Samsung, Apple, Huawei or Google and analyse its customer experience strategy within one specific country in which the company operates. The report is written from the perspective of a CX consultant and is intended for the Board of Directors of the selected company. Relevant customer experience concepts, academic literature and practical business applications should be incorporated throughout the report. The first part of the report examines the concept of customer experience and its importance to business success. The analysis should consider the role of CX, the mutual benefits created for the company and its customers, the effect of CX on business and financial performance, and specific examples of how the selected brand has used customer experience to achieve competitive advantage. The second part evaluates how the selected company delivers a seamless omnichannel customer experience. This requires consideration of customer personas and customer journey mapping and their contribution to developing an effective customer strategy. Students must create a detailed customer persona based on research and data analysis, covering the profile, goals, pain points and motivations of the selected customer. A customer journey map should then identify stages, needs, activities, feelings, pain points and opportunities for improvement. The report should evaluate the effectiveness of the company's customer journey and suggest practical improvements. The words contained within the recommended customer persona and customer journey map templates are excluded from the 2,500-word limit. The third part evaluates the effectiveness of the company's use of customer experience metrics to measure the quality of its relationship with customers. Students must discuss three CX metrics covered in the module and critically assess their benefits, limitations and relevance to the selected company. The analysis should explain why these metrics would be useful for measuring the mutually beneficial relationship between the company and its customers. The final part critically reflects on the company's ability to create a customer-centric culture in an increasingly digital environment. This includes evaluating CX leadership and CX governance, as well as one additional critical success factor such as people, CX structure, strategy and process, or innovation. The report should conclude by evaluating the overall quality of the company's relationship with its customers and proposing practical ways to improve customer experience in the era of increasing digitalisation. The assessment addresses four learning outcomes relating to the importance of customer experience, organisational CX performance metrics, seamless omnichannel customer journeys and customer experience strategies in the context of rapid digitalisation. The submission must use Harvard referencing and an academic business-report style.

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Academic and Employability Skills and Research Methods and Masters Dissertation 1,800 words

Personal Development Plan: Academic, Employability and Career Development

This assessment requires students to develop a Personal Development Plan (PDP) related to their chosen field of work and future career pathway. The assignment is designed to support the development of academic, employability, professional and research-related skills while encouraging students to critically reflect on their current capabilities and identify areas for further development. The assessment consists of three interconnected components presented together as one document. The first component is a 750-word academic report that critically evaluates employment and entrepreneurial opportunities within the student's chosen field of work. Students are expected to use a range of relevant academic and professional sources to investigate the knowledge and skills required for their chosen career area, available employment opportunities, entrepreneurial opportunities and the challenges associated with the field. The chosen field must be clearly related to the student's study pathway specialism. The report should be presented in an appropriate academic structure, including an introduction and conclusion. The second component is a 750-word self-analysis and action plan. Students are required to critically reflect on their own strengths and weaknesses in relation to their chosen field of work or career path. The reflection should be supported by relevant academic and professional literature and should demonstrate awareness of personal qualities, employability requirements and areas requiring further development. Students must identify three specific action points for personal development that will enhance their readiness for their career goals. The third component is a portfolio of completed tasks, included as appendices to the assessment. These tasks provide evidence of the student's development and include activities relating to the chosen field of work, report planning, self-analysis and a SMART action plan. Evidence of completed tasks and Turnitin submission receipts is also required. The assessment encourages students to develop awareness of their personal strengths and weaknesses, engage in continuing self-development and build the skills required for employment and career progression. It also relates to research, employability and entrepreneurship competencies, including knowledge of hard and soft skills, systematic planning, critical analysis, professional development, ethical awareness, self-direction and independence. The complete assessment has a 1,500-word limit with a permitted variation of plus or minus 10%. Part 1 and Part 2 each contribute 40%, while the portfolio tasks contribute 10% and professional presentation contributes 10%. The assignment should be submitted as one professionally presented document and follow APA style guidelines.

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Global Supply Chain Management 1,800 words

Suez Canal Blockage: A Case Study of Global Supply Chain Disruption

This individual report examines the challenges faced by global supply chains as a result of the Suez Canal blockage and critically evaluates the factors that affected supply chain performance during the disruption. The assignment uses the Suez Canal blockage as a case study to explore the wider principles and practices of global supply chain management, with particular attention to supply chain disruption, risk management, resilience, logistics, supplier relationships and integrated supply chain performance. The report requires students to conduct preliminary research into the Suez Canal blockage and use relevant academic and practical sources to identify the major challenges created by the disruption. The case study focuses on the six-day stranding of the Ever Given and the resulting disruption to international supply chains and global trade. The assessment considers how a disruption at a strategically important global trade route can create wider consequences for organisations, logistics networks and supply chain operations. The analysis should identify the key factors that influenced supply chain performance and critically evaluate the effectiveness of the solutions implemented to resolve the disruption. Relevant global supply chain management theories, models and concepts should be clearly defined and applied to the case rather than simply described. The report should demonstrate an understanding of fundamental supply chain principles and consider how evolving trends and global issues can affect supply chain operations. The assignment also encourages consideration of important supply chain management areas covered within the unit, including risk management, resilience, outsourcing, supplier planning and selection, relationship management, supply chain integration, demand management, order management and customer service. These concepts should be connected to the Suez Canal blockage to provide a critical assessment of the challenges and possible approaches to improving supply chain resilience. The report must be presented in a formal and logically coherent report format and should provide evidence of critical reasoning through a wide range of relevant academic and practical sources. The conclusion should draw together the main findings, while recommendations should propose realistic approaches for addressing the supply chain issues identified in the case. The assessment is worth 30% of the overall unit mark and requires an individual report of 1,800 words, with a permitted variation of ±10%. The report is assessed across four main areas: use of theory and frameworks (25%), analysis and evaluation (30%), conclusions and recommendations (20%), and structure, presentation and referencing (25%). The marking criteria emphasise the application of relevant theoretical concepts, critical evaluation of academic and practical sources, a clear connection between theory and practice, realistic recommendations, logical structure, and appropriate in-text citations and referencing.

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International Human Resource Management 800 words

A Comparative Analysis of Cultural Factors Shaping Human Resource Staffing Strategies in International Enterprises

This assignment presents a comparative analysis of the cultural and institutional factors that influence human resource staffing and recruitment strategies in international enterprises. The case study focuses on VetDopomoga, a Ukraine-based international veterinary clinic chain that is considering international expansion into either the United Kingdom or India. The assignment requires an assessment of the potential benefits and challenges associated with operating in each market and the development of evidence-based recommendations for the organisation's international expansion. The poster begins by comparing the cultural and institutional environments of Ukraine, the United Kingdom and India. The analysis considers factors such as communication styles, hierarchy and power distance, individualism and collectivism, time orientation, labour-market characteristics and the regulatory and employment context. These factors are considered in relation to their potential influence on human resource practices, particularly recruitment. The assignment also requires the application of an international HR staffing strategy approach. Students must consider ethnocentric, polycentric, regiocentric and geocentric approaches and use their analysis to recommend which of the two potential markets VetDopomoga should enter first and which should be considered as the second market. The recommendation must be supported by evidence and clear justification. A cultural theory must also be selected and applied to analyse two relevant cultural dimensions. The available theoretical approaches include the Cultural Intelligence framework, Erin Meyer's Culture Map, the GLOBE Project and Hofstede's Cultural Dimensions Theory. The selected theory is used to examine the benefits and challenges of recruitment practices in Ukraine, the United Kingdom and India. The assignment further requires consideration of one major recent cultural, economic or political event affecting each country and an evaluation of how these developments may influence recruitment and international HR practices. Students must research best-practice recruitment examples from international veterinary enterprises operating in the UK and India and identify practices that VetDopomoga could adopt or adapt. Finally, the poster must provide a clear recommendation regarding the order of market expansion and identify three supporting recommendations. Visual elements such as diagrams, icons and charts should be used to communicate the findings clearly and concisely. The final poster should be no more than two pages and approximately 800 words, excluding illustrations, with appropriate Harvard in-text citations and a full reference list.

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Advanced Artificial Intelligence

CW1: Applying advanced AI methods for analysing text documents

This coursework is an individual practical assessment for the Advanced Artificial Intelligence module, focusing on the application of advanced artificial intelligence, natural language processing (NLP), natural language understanding (NLU), and neural network techniques to analyse text documents. The coursework uses a provided social-media dataset containing more than 89,000 posts associated with 947 news headlines. Each social media post is treated as an individual text document and is labelled as either real or fake according to the relationship between the linked news headline, its ground-truth status, and majority annotator agreement. The assessment consists of two main tasks. The first task focuses on the identification of fake text documents. Students are required to perform descriptive data analysis and NLP preprocessing before transforming text into numerical feature representations suitable for neural network classification. Students must design and implement both a Multi-Layer Perceptron (MLP) network and a deep learning neural network to classify documents as real or fake. The assessment requires justification of the selected architectures, including inputs, layers, neurons, activation functions and outputs. Students must also experiment with hyperparameters, evaluate model performance using appropriate metrics, compare different models, select suitable models, and save trained models for later demonstration. The second task focuses on topic discovery using natural language understanding techniques. Students are required to apply text-processing methods such as tokenisation, stop-word removal, lemmatisation or stemming and experiment with at least two different text representation strategies. Possible approaches include Bag of Words, TF-IDF, Latent Dirichlet Allocation, word vectors and word embeddings. The discovered topics must be analysed and interpreted in relation to the document content, associated news headlines, and class labels. The assessment is supported by a practical bench demonstration and a maximum of seven PowerPoint slides covering the design, model improvement process, performance evaluation and discussion of results. Students must submit their own Python code and presentation through Blackboard and demonstrate their saved models without retraining them during the demonstration. The marking scheme allocates 45% to fake text document identification, 35% to topic discovery using NLU, and 20% to the structure, organisation, professionalism and question-and-answer performance of the demonstration.

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International Business Strategy 250 words

Individual Reflection on Case Study Discussion – International Business Strategy

This assignment is an individual reflective assessment for the International Business Strategy module. It focuses on developing students’ ability to critically reflect on their learning experiences and identify how learning from classroom discussions can improve their future academic and professional performance. The assessment is based on a Case Study Discussion undertaken during one of the teaching weeks from Week 5 to Week 8. Students are required to select one of the case studies discussed during the relevant seminar sessions and reflect on their learning from the discussion. The case-study discussions provide an opportunity to explore important issues in the business world, apply concepts introduced through Canvas preparation and face-to-face teaching, and exchange ideas with tutors and peers. The reflection therefore connects theoretical knowledge with practical business situations and encourages students to consider how strategic management concepts can be applied to real-world organisations. The reflective task requires students to explain the topic and case study discussed during their selected week, identify what they learned from the discussion, and consider how the experience helped them develop their ability to apply theories to their chosen company. Students should also reflect on their key takeaways, what went well during the discussion, challenges they encountered, and what they would change if they were to repeat the experience. The reflection should be between 150 and 250 words and should use an appropriate reflective framework, such as Gibbs' Reflective Cycle or Kolb’s Experiential Learning Cycle, to structure the discussion. Harvard referencing should be used where applicable. The assessment develops critical reflection, strategic thinking, international business understanding and the ability to connect academic concepts with practical business cases. The assessment is worth 15% of the module and is submitted through Canvas. The marking criteria consider the quality of reflection, critical analysis, personal learning insights, presentation and structure, intellectual curiosity, referencing, content and discussion.

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Time Series Modelling

Time Series Modelling Case Study – Oil Price Forecasting

This individual Time Series Modelling Case Study focuses on analysing and forecasting oil price data using established time-series techniques and an alternative modelling approach. The assessment requires students to work with daily oil price information covering the period from 2024 to 2026 and investigate the underlying patterns, stationarity and forecasting behaviour of the data. The first part of the assignment involves exploratory data analysis and time-series modelling using an ARMA-based approach. Students are required to create appropriate visualisations of the data, perform exploratory analysis and conduct tests for non-stationarity, including relevant stationarity diagnostics such as ADF, ACF and PACF analysis and differencing where required. An ARMA model must then be defined, with suitable model parameters identified using the AIC likelihood approach. The assessment requires the student to examine possible combinations of model parameters, assess model residuals, evaluate model performance using appropriate metrics such as RMSE, and produce forecasts extending 24 months into the future. Confidence intervals must also be included with the forecasts. The second part requires students to investigate an alternative modelling solution for the same oil-price time-series data. Possible approaches discussed in the assignment include models such as LSTM and Prophet. Students are expected to conduct a literature review relating to the selected alternative model, build and apply the model, tune relevant hyperparameters where appropriate, generate 24-month forecasts, create suitable visualisations and calculate appropriate evaluation metrics. The final part of the assessment requires a 6–8 page report describing the modelling process, forecasts, analysis and inferences. The report should explain the reasoning behind the analytical and modelling choices rather than simply presenting numerical results. Students are expected to critically discuss why particular approaches were selected, how the modelling decisions may have influenced the results, how forecasts compare with subsequently collected real data where available, and what improvements could be made in future work. The assessment evaluates both the technical implementation and the quality of the written analysis. The code component assesses completion of the modelling and forecasting tasks, stationarity testing, the alternative solution, code quality and annotation. The report component assesses discussion of the analysis and inferences, comparison of the modelling approaches, clarity of interpretation, report structure, appropriate use of figures and suitable academic references. The submission consists of a report in PDF or Word format, with the code submitted separately or through an appropriate repository.

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Global Supply Chain Management 4,200 words

Global Supply Chain Management – Gatwick Airport Northern Runway Expansion

This individual report examines several strategic and operational aspects of the global supply chain associated with the Gatwick Airport Northern Runway expansion. The assessment requires students to investigate the organisation and its current global supply chain challenges, while applying relevant supply chain management theories, frameworks and models to analyse its operations and develop strategic recommendations. The report begins by providing a background of the organisation, with particular attention to its current global supply chain issues and strategic supply chain relationships. Key areas of investigation include risk management, supply chain resilience, outsourcing, supplier planning and selection, supply chain integration, network design, leadership, benchmarking, decision-making, and the application of lean and agile approaches. These areas provide the basis for understanding how the organisation can manage its supply chain effectively within a complex and changing global environment. A critical evaluation of external factors affecting the organisation's global supply chain is also required through the use of a PESTEL analysis. This enables consideration of the political, economic, social, technological, environmental and legal factors that may influence supply chain performance, risks, costs and strategic decisions. The report must then develop key strategic recommendations aimed at optimising the organisation's global supply chain. The recommendations should focus on reducing costs, supporting sustainability, improving operational efficiency and enhancing supply chain resilience. Each recommendation should be supported by appropriate supply chain management theories and models, such as agile supply chain approaches, lean supply chain principles and global sourcing strategies. Students are expected to provide a clear rationale for their recommendations using theoretical insights and relevant academic and professional literature. The assessment places emphasis on critical reasoning, wider reading and the ability to connect supply chain theory with practical organisational issues. A logically structured, professional and business-like report is required, supported by appropriate evidence and Harvard referencing. The marking criteria assess the use of theory and frameworks, critical analysis and evaluation, conclusions and recommendations, and the overall structure, presentation and referencing of the report. The assignment is worth 70% of the unit assessment and has a required length of approximately 4,200 words, with a permitted variation of ±10%. The report should demonstrate an understanding of global supply chain management practices and the ability to apply relevant theories and frameworks to analyse supply chain challenges and develop realistic strategic recommendations.

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Computational Algorithms and Paradigms 1,000 words

Computational Algorithm Analysis – Research Paper Algorithm

This individual coursework for the Computational Algorithms and Paradigms module requires students to thoroughly analyse a computational algorithm proposed in a research paper selected from the list of research papers provided on Canvas. The purpose of the assessment is to develop students' ability to understand, explain and critically evaluate computational algorithms presented in academic research. Students must first identify and describe the computational problem addressed by the selected research paper and clearly state the research questions investigated by the authors. They must then extract the main computational algorithm proposed in the paper and present it in pseudocode. The assessment also requires students to clearly identify the inputs required by the algorithm and the outputs produced by it. The coursework consists of six main analytical sections. The first section focuses on the computational problem and research questions addressed in the selected paper. Students are expected to provide an accurate description of the problem and explain the research questions that the proposed algorithm attempts to address. The second section requires the proposed computational algorithm to be represented using suitable pseudocode. The third section identifies and explains the algorithm's inputs and outputs. The fourth section requires students to explain the proposed algorithm using simple and understandable language. The explanation should demonstrate a clear understanding of how the algorithm operates rather than simply reproducing the description provided in the research paper. The fifth section focuses on analysing the time complexity of the proposed algorithm. Students should evaluate the computational cost of the algorithm and explain its time complexity appropriately. The final section requires a critical evaluation of the algorithm's strengths and weaknesses. Students should identify the advantages and limitations of the proposed approach and discuss potential improvements where appropriate. This section should demonstrate critical thinking about the effectiveness, efficiency and practical applicability of the algorithm. The coursework has a total word count requirement of 800–1,000 words. The inputs and outputs, pseudocode and time-complexity analysis sections are excluded from this word-count limit. The template requires approximately 250 words for the computational problem and research questions, approximately 250 words for the simple explanation of the algorithm, and approximately 300 words for the strengths and weaknesses evaluation. Students must report the word count for sections 1, 4 and 6 after completing the assignment. The submitted work must be original and is subject to plagiarism and collusion checks through Turnitin. The assessment brief also states that generative AI tools may be used for proofreading but are not permitted for creating the coursework content. No figures or images are permitted, and the coursework must be submitted using the provided Word template in DOC or DOCX format.

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1,000 words

Organisational Strategy and Sustainability: Strategic and Sustainability Analysis of Engineers & Planners Company Ltd

This formative Organisational Strategy and Sustainability assessment requires students to act as a management consultant for BPP Consulting Group and provide a strategic and sustainability evaluation of ENGINEERS & PLANNERS COMPANY LTD for its Board of Directors. The task focuses on how internal capabilities, external market forces, sustainability pressures, ethical practices and responsible leadership shape the organisation’s strategy within an increasingly global business environment. Formative Assessment - Organisa… ENGINEERS & PLANNERS COMPANY LTD is described as a Ghanaian-owned mining and construction contracting company, established in 1997 and headquartered in Accra. Its activities include contract mining, road construction, tailings-dam construction, land reclamation and hard-rock mining, with operations in Ghana and Liberia. The company also owns Dzata Cement, a cement manufacturing facility in Tema with an annual production capacity of approximately 2.3 million metric tons. Formative Assessment - Organisa… Formative Assessment - Organisa… The formative task addresses the first two learning outcomes of the summative assessment. LO1 – Strategic Environmental Analysis requires a brief but critical evaluation of the organisation’s internal resources and capabilities together with its external environment. Students should use one internal and one external strategic framework, with examples including PESTEL or Porter’s Five Forces, identify internal competencies, opportunities and threats, and consider how the organisation might respond to dynamic market forces in regions such as the European Union, Asia or North America. Sources of competitive advantage should also be identified from the internal analysis. Formative Assessment - Organisa… Formative Assessment - Organisa… LO2 – Ethical, Sustainable and Responsible Practices requires students to assess how ENGINEERS & PLANNERS COMPANY LTD could integrate CSR, sustainability or ethical practice into its wider business strategy. The brief recommends applying one framework such as the Triple Bottom Line or Sustainable Supply Chain Management. The discussion should connect the sustainability analysis back to the strategic issues identified under LO1. Formative Assessment - Organisa… Formative Assessment - Organisa… Students are also expected to consider how leadership shapes the organisation’s sustainability response, including engagement with stakeholders such as suppliers, customers and NGOs and the influence of regulatory frameworks such as the UN Sustainable Development Goals and relevant European Union legislation. One specific sustainability initiative should be briefly considered, such as product lifecycle management, eco-design, renewable-energy integration or supply-chain transparency. Formative Assessment - Organisa… The recommended report structure consists of an introduction, LO1 Strategic Environmental Analysis, LO2 Ethical, Sustainable and Responsible Practices, and a conclusion summarising recommended strategic and sustainability improvements. Suggested allocations are approximately 50 words for the introduction, 450 words for LO1, 450 words for LO2 and 50 words for the conclusion. Formative Assessment - Organisa… The total submission limit is 1,000 words, with the main body subject to the word-count restriction. The work must use third-person academic writing, professional formatting, appropriate tables and figures, and consistent Harvard citations. Formative Assessment - Organisa… Higher-quality work is expected to go beyond descriptive use of strategic models by critically evaluating the organisation’s internal and external environment, identifying key drivers of change, considering global and local influences on strategic choices, and linking sustainability and responsible-business practices to stakeholder expectations and regulatory pressures. Formative Assessment - Organisa… Formative Assessment - Organisa…

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Research Methods / Project Management / Computer and Information Sciences 3,000 words

Critical Literature Review in Research Methods and Project Management

This Research Methods and Project Management assessment develops students’ ability to search for, evaluate, critically analyse and synthesise academic literature within a computing or information-science research area. Students work within an allocated group to conduct a structured literature search and critically evaluate research papers relevant to an assigned theme, before using the combined group literature corpus to produce an individual literature review. KF7028 - Assessment 1 - Semeste… Each group member must identify and critically analyse a minimum of five academic papers using the supplied Critical Paper Summary template. These individual summaries are then combined into a single group document and shared so that all team members can use the collective body of research. The quality of this component depends on the relevance and academic quality of the selected papers and the depth of critical evaluation rather than simple description. KF7028 - Assessment 1 - Semeste… The main individual component is a 3,000-word critical literature review, worth 60% of the assessment. Students must use the literature identified and summarised through the group activity and critically discuss the research associated with their allocated topic. The review should synthesise the literature into a coherent discussion rather than presenting disconnected paper summaries, demonstrating criticality, clear structure and effective academic writing. KF7028 - Assessment 1 - Semeste… A further 20% is awarded for an individual research and meeting log, maintained through Blackboard. Students are expected to record their research progress, contribution to the group, approach to collaboration and reflections on the literature-review process. Stronger logs demonstrate detailed evidence of active participation, reflective insight and professional collaboration rather than merely listing completed tasks. KF7028 - Assessment 1 - Semeste… KF7028 - Assessment 1 - Semeste… The assessment directly evaluates the ability to apply project-management principles to a computing-related research activity and to search, evaluate and develop a critical literature review. Wider module outcomes also emphasise research techniques, data and information analysis, professional research practice, ethics, risk, legal issues, societal considerations and sustainability. KF7028 - Assessment 1 - Semeste… The marking structure allocates 20% to the combined critical paper analysis, 20% to the research/meeting log and 60% to the individual literature review. Higher-performing work is expected to use high-quality and directly relevant academic sources, demonstrate strong critical analysis, synthesise evidence across the research theme, maintain a professional academic structure and apply accurate Harvard referencing throughout. KF7028 - Assessment 1 - Semeste… KF7028 - Assessment 1 - Semeste… Important for the public Reference Library: the brief states that ChatGPT or other AI tools must not be used to generate text or fill in assessment-template sections. Any AI use that supports the work or thinking must be declared, referenced and accompanied by a prompt log in an appendix. Therefore, this entry should be used only as a high-level public description of the assessment rather than as directly submissible student content. KF7028 - Assessment 1 - Semeste…

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Cybersecurity / Information Security Auditing 3,000 words

Physical Security Audit of University Computing Facilities Using ISO/IEC 27002:2022

This postgraduate information-security coursework requires students to act as an IT Security Auditor working for CyberSAFE Auditors and conduct a professional physical-security audit of computing resources used by students at the University of Greenwich. The audit focuses on public student-study and open computing areas within the Dreadnought and Stephen Lawrence Buildings, with findings evaluated against relevant physical-security controls from ISO/IEC 27002:2022 Section 7. 202526 SL-COMP1431 CWK 2026-am … The project begins with planning and project-control activities. Students must define their audit tasks, plan the work independently and document progress through two Work-in-Progress reports, one produced near the beginning of the project and another approximately halfway through. Each WIP report is limited to 250 words and records completed activities, encountered or anticipated problems, planned next steps and potential risk areas. 202526 SL-COMP1431 CWK 2026-am … The second phase involves practical fieldwork. Students must visit the specified university buildings and decide on suitable audit methods, timetable and evidence-gathering procedures. The audit is restricted to public student areas and must not include staff rooms, seminar rooms or utility areas. Students must also comply with client-imposed constraints, including not communicating with university staff and approaching the audit from the perspective of an ordinary student rather than conducting highly technical operating-system or server-level investigation. 202526 SL-COMP1431 CWK 2026-am … 202526 SL-COMP1431 CWK 2026-am … The final professional audit report evaluates secure areas and equipment security, including physical security perimeters, entry controls, protection of rooms and facilities, working in secure areas, equipment siting, supporting utilities and cabling security. Findings should distinguish between expected controls and observed controls, identify gaps and provide justified recommendations for immediate and future management action. 202526 SL-COMP1431 CWK 2026-am … 202526 SL-COMP1431 CWK 2026-am … Assessment places particular emphasis on practical audit methodology, secure-area analysis, equipment security, audit conclusions, gap analysis, professional reporting and the two WIP reports. 202526 SL-COMP1431 CWK 2026-am … Overview word count: approximately 355 words. AI-use note: the brief states that this coursework does not lend itself to reliance on AI-based applications such as ChatGPT and emphasises original analysis, fieldwork and proper attribution of sources. 202526 SL-COMP1431 CWK 2026-am …

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Enterprise Business Start-up: Sustainable Business Plan, Fundraising Strategy and Entrepreneurial Reflection

Entrepreneurship, Business Start-up, Business Plan, Business Idea, Innovation, Sustainable Business, Market Gap, Market Research, Competitor Analysis, Customer Segmentation, Customer Profiles, Product Development, Marketing Strategy, Marketing Communications, Business Model, Costing, Pricing Strategy, Sales Forecasting, Revenue Model, Financial Planning, Founding Team, Core Competencies, Fundraising Strategy, Venture Capital, Angel Investment, Entrepreneurial Tendency, GET Test, Entrepreneurial Self-Assessment, Start-up Finance, Business Pitch

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Computer Science / Algorithms / Parallel Computing / Clustering

Parallel Algorithms for Hierarchical Clustering: Single-Link, Minimum Spanning Trees and Parallel Architectures

This research paper investigates parallel algorithms for hierarchical clustering, a clustering technique in which individual data points initially form separate clusters and the closest clusters are repeatedly merged until a hierarchical tree structure, or dendrogram, is formed. The paper reviews important sequential clustering algorithms, surveys previous parallel approaches and proposes parallel methods for several commonly used inter-cluster distance metrics. Prims_algorithm_for_hierarchica… The paper distinguishes between graph-based metrics and geometric metrics. Graph metrics include single-link, average-link and complete-link clustering, while geometric metrics include centroid, median and minimum-variance methods. It also discusses the Lance–Williams updating formula, which provides a general framework for updating inter-cluster distances after agglomeration. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… A major focus is the relationship between single-link hierarchical clustering and the Euclidean minimum spanning tree. The paper explains that the cluster hierarchy for single-link clustering can be obtained from a minimum spanning tree, making minimum-spanning-tree algorithms highly relevant to efficient hierarchical clustering. It presents practical single-link algorithms with O(n²) time complexity and discusses space requirements and nearest-neighbour update properties. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… The paper also examines algorithms for metrics satisfying the reducibility property, where nearest-neighbour chains can be used to efficiently determine which clusters to merge. Minimum-variance and graph-based metrics satisfy this property, while centroid and median metrics do not necessarily do so. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… For more general clustering metrics, the paper describes priority-queue-based algorithms with O(n² log n) sequential time complexity. It then reviews previous parallel work, including parallel implementations of SLINK, Ward’s method and Prim’s minimum spanning tree algorithm. The cited parallel Prim implementation achieves O(n log n) time when sufficient processors are available. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… The core contribution is a set of parallel algorithms for hierarchical clustering on PRAM, butterfly and tree architectures. For single-link clustering, the paper shows how a parallel minimum-spanning-tree approach can be used and reports an O(n log n) running time using n/log n processors. Similar optimal results are described for centroid, median and minimum-variance clustering, while average-link and complete-link methods are more difficult to optimise on local-memory architectures. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… Overall, the paper demonstrates how hierarchical clustering can be accelerated through parallel computation while preserving the computational structure of different clustering metrics. Its main themes include minimum spanning trees, Prim’s algorithm, single-link clustering, nearest-neighbour methods, PRAM computation, parallel data structures and asymptotic complexity analysis. Prims_algorithm_for_hierarchica… Important: because this file is a journal research paper rather than a university assessment brief, fields such as module name, academic level, assignment type and formal word count do not genuinely apply.

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Calculus and Optimisation: Python Implementation of Gradient Descent, Derivatives and Polynomial Regression

This Calculus and Optimisation technical exercise demonstrates the implementation of mathematical and machine-learning concepts using Python. The document is organised as a set of code fragments that must logically work together to perform symbolic calculus, numerical optimisation, physical modelling and polynomial regression. The material uses libraries including NumPy, SymPy, Matplotlib and Scikit-learn, linking mathematical theory with practical computational implementation. Jigsaw_Puzzle_Calculus_Original… A central component is the implementation of gradient descent for linear regression. The supplied function calculates predictions, evaluates prediction errors, computes gradients and updates model parameters iteratively using a configurable learning rate. Mean squared error is recorded during optimisation, and a tolerance-based stopping condition is used to terminate the algorithm when successive cost values change by only a very small amount. Jigsaw_Puzzle_Calculus_Original… Synthetic linear-regression data is generated using a fixed NumPy random seed to support reproducible experimentation. A bias column is added to the feature matrix, initial parameter values are randomly generated, and the custom gradient-descent function is then executed to estimate the intercept and slope of the relationship. Jigsaw_Puzzle_Calculus_Original… The document also demonstrates symbolic differentiation and optimisation using SymPy. A cubic polynomial is defined and differentiated to obtain both its first and second derivatives. Critical points are identified by solving where the first derivative equals zero, while the second derivative is evaluated at each critical point to determine whether the point represents a local minimum, local maximum or saddle point. Jigsaw_Puzzle_Calculus_Original… Jigsaw_Puzzle_Calculus_Original… A further section applies mathematical formulas to projectile motion. Using a specified initial velocity, launch angle and gravitational acceleration, the code calculates both maximum projectile height and horizontal range. This component illustrates how calculus-related mathematical relationships can be translated directly into executable computational models. Jigsaw_Puzzle_Calculus_Original… The final major element explores polynomial regression. Synthetic nonlinear data is generated from a cosine-based function with added random noise. Scikit-learn pipelines are then used to compare polynomial models of degrees 1, 4 and 15. The models are fitted to the synthetic dataset and visualised against the underlying true function, allowing comparison of model complexity and illustrating concepts such as underfitting and overfitting. Jigsaw_Puzzle_Calculus_Original… Jigsaw_Puzzle_Calculus_Original… Overall, the exercise integrates calculus, optimisation, numerical methods and machine-learning modelling through Python. It provides practical experience with differentiation, critical-point analysis, iterative optimisation, mathematical simulation, regression modelling and visualisation. Important: because this file does not identify a university, assessment weighting, academic level, reference style or required word count, those fields should remain Not specified / Not applicable rather than being invented.

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Entrepreneurial Marketing

Entrepreneurial Marketing Business Idea Pitch: Market Opportunity, Value Proposition and Venture Viability

This Entrepreneurial Marketing assessment requires students to identify, research and present an entrepreneurial business idea that either addresses an identified customer need or exploits a recognised market opportunity. The idea may involve a new product or service and can be developed either as a personal start-up opportunity or as a new business proposition for an existing organisation. CW1 Business Idea Pitch Present… Students are expected to construct a concise business case around four core elements: the proposed business idea, the identified need or opportunity and resulting value proposition, an overview of the relevant market, and an appropriate entrepreneurial marketing strategy. The pitch should demonstrate how the proposed offering creates value and why the opportunity is commercially credible. CW1 Business Idea Pitch Present… The assessment provides three presentation routes. Students may deliver the pitch live to a panel, submit a five-minute narrated PowerPoint with a recorded response to the question of why the idea is strong, or submit the narrated presentation while also participating in the live Business Ideas Showcase. CW1 Business Idea Pitch Present… Students are expected to prepare approximately 6–10 PowerPoint slides, use in-text citations when external evidence is presented, and include a reference slide. The pitch should be concise, professional and supported by appropriate market research and business evidence. CW1 Business Idea Pitch Present… The marking criteria assess presentation and professionalism, verbal delivery, innovation and value proposition, market research and analysis, entrepreneurial marketing strategy, and overall business-case viability. Each of the main analytical components carries substantial weighting, with market research, marketing strategy, innovation and viability each contributing significantly to the final result. CW1 Business Idea Pitch Present… Overall, the assessment integrates opportunity recognition, value proposition development, market analysis, entrepreneurial marketing, venture viability and professional pitching skills within a practical start-up or business-development context. The brief specifies Cite Them Right Harvard referencing. CW1 Business Idea Pitch Present… 2) CW2 – Reflective Essay Field Content to enter Title Reflective Analysis of Entrepreneurial Capabilities, Product Development and Network-Based Opportunity Creation University University of Hertfordshire Subject Entrepreneurial Marketing / Entrepreneurship / Reflective Practice Module name Entrepreneurial Marketing Academic level Masters / Postgraduate Academic year 2025–2026 Assignment type MS Reflective writing Reference style Harvard Word count 1,000 words ±10% Amount (₹) Enter your internal project amount Key topics Entrepreneurial Marketing, Entrepreneurial Capabilities, Entrepreneurship, Reflective Practice, Product Development, Service Design, Opportunity Recognition, New Product Development, Teamwork, Networking, Business Start-up, Entrepreneurial Potential, Intrapreneurship, Personal Development, Business Application, Reflexive Practice, Entrepreneurial Confidence, Capability Development, Recommendations, Professional Reflection The assessment is an individual 1,000-word reflective essay worth 30% of the module. CW2 Reflective Essay (Individua… Assignment overview — ready to paste This Entrepreneurial Marketing reflective assessment requires students to critically evaluate their own entrepreneurial and intrapreneurial capabilities using learning from the module together with relevant life and work experience. The essay should use appropriate academic theories and frameworks to identify key strengths and development areas and make clear recommendations for improving future entrepreneurial potential. CW2 Reflective Essay (Individua… A major element of the reflection concerns the principles involved in designing a new product or service to meet an identified need. Students are expected to consider how entrepreneurial ideas are developed, how opportunities are recognised and how entrepreneurial capabilities influence the process of converting an idea into a viable proposition. CW2 Reflective Essay (Individua… The assessment also requires critical reflection on the importance of teams and networks in developing business-start-up opportunities and designing new services. The module learning outcomes emphasise the role of collaborative performance, networking and reflexive practice in strengthening entrepreneurial confidence and capability. CW2 Reflective Essay (Individua… Students should move beyond simple personal description and critically analyse their capabilities with reference to academic evidence. At least five academic references are required, and the work should use Cite Them Right referencing. CW2 Reflective Essay (Individua… The marking scheme allocates equal weighting to five areas: presentation, structure and reflective style; content and findings; intellectual curiosity and business application; critical analysis; and recommendations, with each area worth 20%. CW2 Reflective Essay (Individua… Overall, the assessment integrates self-reflection, entrepreneurial capability analysis, product and service design, team and network performance, academic theory and personal development planning. Its purpose is to demonstrate how reflective learning can support stronger entrepreneurial judgement, confidence and future business practice. The brief requires Cite Them Right Harvard referencing. CW2 Reflective Essay (Individua…

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Critical Analysis of Computational Algorithms: Research Paper Evaluation and Complexity Analysis

This postgraduate Computer Science coursework requires students to undertake a critical technical analysis of a computational algorithm presented in a prescribed academic research paper. Students select one paper from the available options and demonstrate that they understand both the research problem addressed by the authors and the algorithmic solution proposed. The assessment contributes 30% of the overall module grade and is completed individually. assignment The available research papers cover several algorithmic topics, including an improved Dijkstra shortest-path algorithm for sparse networks, a modified merge-sort approach for large-scale datasets, parallel merge sort with load balancing, and a Prim-based algorithm for hierarchical clustering. Students must extract the principal algorithm from their selected paper and explain its purpose, inputs, outputs and operating procedure. A major component involves identifying the research question and computational problem addressed by the selected study. Students then reproduce or extract the proposed algorithm in pseudocode form and clearly identify the information supplied to the algorithm and the outputs it generates. The algorithm must also be explained step by step using straightforward language so that its operation can be understood without relying exclusively on formal notation. The coursework further requires a detailed time-complexity analysis, demonstrating understanding of how computational requirements grow with input size and how the proposed technique compares with alternative or conventional approaches. Students must critically evaluate the algorithm’s strengths, weaknesses, performance characteristics and limitations, and suggest potential improvements where appropriate. The marking rubric gives substantial emphasis to five areas: identifying the computational problem and research questions, extracting the proposed algorithm, identifying inputs and outputs, explaining the algorithm clearly, analysing its time complexity, and critically evaluating its strengths and weaknesses. assignment The written submission must be 800–1,000 words, although the inputs/outputs, pseudocode and time-complexity sections are excluded from that limit. Figures and images are not permitted, and the work must be submitted using the prescribed coursework template in DOC/DOCX format. Overview word count: approximately 340 words. AI-use note: the guideline permits generative AI only for proofreading. AI tools are explicitly not permitted to create the assessed work itself. assignment

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Artificial Intelligence / Natural Language Processing / Deep Learning

Applying Advanced AI Methods for Analysing Text Documents

This Advanced Artificial Intelligence coursework requires students to implement and evaluate natural language processing, natural language understanding and neural-network techniques for analysing text documents. The assessment uses a supplied social-media dataset containing more than 89,000 posts linked to 947 news headlines, with each post labelled as real or fake through a combination of headline ground truth and majority-vote annotation. Each social-media post is treated as an individual text document for classification and topic-analysis purposes. CMP_6059B_7059B_2025_26_CW1-pre… The first major task focuses on identifying fake text documents. Students must preprocess the text using appropriate NLP techniques, transform documents into numerical feature representations and experiment with alternative preprocessing approaches to determine which performs best. A separate unseen test set must be reserved to evaluate generalisation, while the remaining data is used for training both shallow and deep neural-network classifiers. Students are expected to explain and justify how the data is split. CMP_6059B_7059B_2025_26_CW1-pre… Students first design a multi-layer perceptron (MLP) capable of predicting whether documents are real or fake. The architecture must be justified in terms of input dimensions, number of layers, neuron counts, activation functions and outputs. A second deep-learning neural network must then be developed for the same classification problem, with justification of the chosen network structure, layer types, activations and other configuration decisions. CMP_6059B_7059B_2025_26_CW1-pre… For both networks, students train baseline models and select three hyperparameters considered most important for improving performance. These hyperparameters must be tuned systematically, with visuals prepared to show the experimentation process and resulting performance changes. Appropriate evaluation metrics are then used to compare the trained models. The strongest MLP and deep-learning models must be saved so that they can be loaded and tested on unseen data during the final demonstration without retraining. CMP_6059B_7059B_2025_26_CW1-pre… The second task focuses on topic discovery using NLP and NLU techniques. Students perform syntactic preprocessing such as tokenisation, stop-word removal and lemmatisation or stemming, and experiment with at least two different text-representation approaches. Suggested methods include Bag of Words, TF-IDF, LDA, word vectors and word embeddings. Students must interpret the discovered topics and explain how those topics relate to document content, linked news headlines and class labels. The best topic-discovery model or models must also be saved for live analysis during the demonstration. CMP_6059B_7059B_2025_26_CW1-pre… The assessment is completed through a bench demonstration, supported by a maximum of seven PowerPoint slides. The slides should document the system design, model-improvement process, performance evaluation and discussion of results for both fake-document classification and topic discovery. Students also submit a ZIP file containing only their Python source files. The demonstration lasts up to 15 minutes, consisting of approximately 10 minutes for presentation and technical demonstration followed by 5 minutes for questions and transitions. CMP_6059B_7059B_2025_26_CW1-pre… The marking scheme allocates 45% to fake-document identification, including descriptive analysis, preprocessing, MLP design and deep-learning design; 35% to topic discovery, including preprocessing, model development and interpretation; and 20% to the structure, organisation, professionalism and Q&A quality of the demonstration. CMP_6059B_7059B_2025_26_CW1-pre… Important for the public Reference Library: the brief explicitly states that the use of Large Language Models or generative AI to produce any part of the submission is strictly prohibited, including code, data processing, testing, writing or PowerPoint content. Therefore, this entry should remain only a high-level public description of the assessment and should not be presented as material intended for direct student submission. CMP_6059B_7059B_2025_26_CW1-pre…

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Marketing / Consumer Marketing 1,987 words

MindBand: A Creative Marketing Plan for a Mental Wellbeing Wearable in the UK Smart Device Market

This postgraduate marketing report develops a creative marketing plan for MindBand, a proposed smart wearable designed to support mental wellbeing and emotional regulation in the UK wearable-device market. The assessment responds to a brief requiring students to identify an unmet product need, create an original product concept and apply strategic marketing principles to establish how the innovation could attract consumers in a highly competitive smart-device industry. Reassessment-Individual Assignm… The analysis identifies a potential gap between mainstream fitness-focused wearables and consumers seeking discreet, everyday support for stress, emotional wellbeing and cognitive fatigue. MindBand is positioned as a minimalist wrist-worn device that uses biometric indicators such as heart-rate variability, skin conductance and temperature to identify stress-related patterns and provide context-sensitive interventions. Unlike conventional wearables that primarily display performance data, the concept emphasises behavioural support, simplicity and low-effort interaction. Creative Marketing Plan for a P… Creative Marketing Plan for a P… The marketing plan targets UK professionals aged approximately 30–55, particularly individuals experiencing high cognitive workloads, digital fatigue and work-life pressures. The proposed value proposition focuses on personalised emotional support, discretion and ease of use rather than extensive fitness functionality. This positioning is reinforced through a calm, trust-oriented brand identity intended to distinguish MindBand from performance-led smartwatch and fitness-tracker brands. Creative Marketing Plan for a P… Creative Marketing Plan for a P… The communications strategy adopts a digital-first approach, using educational content, podcasts, professional experts, thought leadership, paid media and customer testimonials to build credibility and awareness. Distribution is primarily direct-to-consumer through e-commerce, supplemented by partnerships with corporate wellbeing programmes and healthcare providers. A premium-value pricing strategy and optional subscription-based services are proposed to support recurring revenue and continued product development. Creative Marketing Plan for a P… The report also considers performance measurement, brand equity, customer retention, privacy, informed consent and responsible use of biometric data. Overall, the work integrates product innovation, consumer behaviour, segmentation, positioning, communications, pricing, distribution and ethical marketing into a coherent smart-wearable marketing proposal.

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International Business / Strategic Management 200 words

Individual Reflection on Tencent’s Strategic Reorganisation and International Business Strategy

This International Business Strategy assessment is an individual reflective exercise based on a case-study discussion undertaken during Weeks 5–8 of the module. Its purpose is to develop students’ ability to critically reflect on learning experiences and use that reflection to improve future academic and professional performance. Students participate in approximately 30-minute seminar discussions in which theoretical concepts from the module are applied to real-world business cases with tutors and peers. IBS-0901-2025-+Reflection2-Ref For this entry, the selected case is Tencent: “third time lucky?”. The case examines how Tencent evolved from a Chinese instant-messaging company into a major technology group spanning messaging, gaming, entertainment, investment and cloud services. It focuses particularly on three major organisational reorganisations undertaken in 2005, 2012 and 2018 as the company attempted to address increasing organisational complexity, coordination problems, changing technologies and new strategic priorities. The 2005 restructuring responded to Tencent’s growing scale by dividing the organisation into major business and platform-development groups. By 2012, further growth and the success of products such as WeChat had created new organisational complexity, leading to a structure organised around seven distinct business groups. The case highlights that this arrangement subsequently contributed to a “silo culture”, creating difficulties in sharing ideas, data, code and customers across business units. The 2018 reorganisation responded to a strategic shift toward the “industrial internet”, including greater emphasis on cloud services, business-to-business solutions and digital transformation. Tencent reorganised around six major groups, including Cloud and Smart Industries, Platforms and Content, Interactive Entertainment, Corporate Development, WeChat, and Technology and Engineering, while also establishing a technical committee intended to improve internal coordination and data sharing. The case asks students to consider both the strategic rationale for each restructuring and whether the 2018 changes adequately addressed Tencent’s organisational challenges. The reflection itself must be between 150 and 250 words. Students should explain what the week’s topic and case study were about, what they learned from the discussion, how the conversation helped them apply theory to their final report, and what key insights they gained. They should also reflect on what went well, what challenges were encountered and what they would change if repeating the session. At least one reflective framework, such as Gibbs’ Reflective Cycle or Kolb’s Experiential Learning Cycle, must be applied. IBS-0901-2025-+Reflection2-Ref The wider learning outcomes emphasise strategic management theory, internationalisation, internal and external environmental influences, critical analysis of international organisations and the use of analytical tools to evaluate strategic options. The task therefore combines strategic thinking, international business analysis and reflective professional development. IBS-0901-2025-+Reflection2-Ref The accompanying Tencent case specifically asks students to consider why each major reorganisation occurred, whether the 2018 restructuring adequately addressed Tencent’s challenges, and what additional “hard” and “soft” implementation measures might have been necessary. Case+study+7

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Digital Marketing / Marketing Analytics / Data-Driven Marketin

Data-Driven Marketing Analytics: Google Analytics 4 and Google Merchandise Store Campaign Analysis

This Data Driven Marketing assessment requires students to develop practical digital analytics skills and apply them to the evaluation of a real-world marketing campaign. The assessment combines professional training through LinkedIn Learning with a recorded executive-level presentation based on data from the Google Analytics 4 Demo Account for the Google Merchandise Store. The aim is to analyse campaign performance, interpret relevant marketing KPIs and present actionable recommendations that senior executives and managers can use for decision-making. CW 1_ LinkedIn Learning and Rec… The first task requires completion of two LinkedIn Learning courses: Google Analytics 4 (GA4) Essential Training and Advanced Google Analytics. Students must submit the certificates of completion as evidence of developing the foundational and advanced skills required for digital marketing analysis. CW 1_ LinkedIn Learning and Rec… The second task places the student in the role of a digital marketing executive for the Google Merchandise Store. Students select and analyse a digital marketing campaign using GA4 demo-store data and then create a 10-minute recorded presentation, with a tolerance of ±2 minutes, providing evidence-based recommendations for improving campaign performance. CW 1_ LinkedIn Learning and Rec… The main presentation is limited to 12 slides and should include an executive summary, key findings and insights, recommendations, actionable steps, and references or appendix material. An additional 4–6 appendix/reference slides may be used for supporting charts, graphs and data. Recommendations must be linked directly to analytical evidence and aligned with the campaign's overall marketing objectives. CW 1_ LinkedIn Learning and Rec… The analysis should examine relevant marketing performance indicators, including click-through rate, conversion rate, cost per acquisition, return on ad spend and user-engagement measures such as bounce rate, session duration, pages per session and retention patterns. CW 1_ LinkedIn Learning and Rec… Students are expected to move beyond descriptive reporting and develop strategic recommendations concerning budget reallocation, creative optimisation, audience targeting and funnel performance. The presentation should identify underperforming and high-performing channels, evaluate audience segments, examine points of user drop-off and propose practical interventions to improve conversion and campaign efficiency. CW 1_ LinkedIn Learning and Rec… The marking scheme gives 20 points for LinkedIn Learning certification, 35 points for executive communication and structure, 35 points for data analysis and insight generation, and 10 points for references and appendices. CW 1_ LinkedIn Learning and Rec… CW 1_ LinkedIn Learning and Rec… Overall, the assessment integrates GA4 skills, campaign analytics, KPI interpretation, data visualisation, strategic recommendation development and executive presentation skills within a practical digital-marketing context. The brief also requires Cite Them Right Harvard referencing. CW 1_ LinkedIn Learning and Rec…

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Entrepreneurship / Leadership and Management 3,500 words

Entrepreneurial Practice: Strategic Analysis, New Venture Development and Professional Reflection

This individual Entrepreneurial Practice assessment requires students to critically analyse a real organisational issue using one of the approved employer case studies and develop an entrepreneurial business proposal aligned with the organisation’s needs. The complete assessment is structured as a 3,500-word-equivalent portfolio consisting of a written report, briefing notes, a narrated PowerPoint presentation and a professional reflection. Entrepreneurial Practice Assign… Task 1 is a 1,500-word organisational analysis worth 30% of the marks. Students critically examine the challenges facing the selected organisation using appropriate strategic-analysis tools. They must also evaluate the organisation’s leadership models and communication strategies and assess their impact on employees, organisational culture and performance. The section concludes with three justified recommendations intended to improve organisational performance. Entrepreneurial Practice Assign… Task 2A consists of 1,000-word briefing notes focused on a proposed entrepreneurial venture. Students critically appraise the stages of entrepreneurial practice from idea generation through to delivery, including the benefits of the proposed venture and suitable funding sources. The task also requires analysis of business risk-management strategies and critical evaluation of the entrepreneurial traits, characteristics, skills and competencies needed to position the proposed venture strategically. Entrepreneurial Practice Assign… Task 2B converts the business proposal into a short narrated PowerPoint pitch. The presentation communicates the rationale and organisational benefits of the business idea, funding opportunities, key risks and mitigation approaches, and the entrepreneurial competencies needed for successful implementation. The intended audience includes employees, managers, senior management and the Board of Directors, so professional communication and persuasive presentation are important. Entrepreneurial Practice Assign… Task 3 is a 500-word personal and professional reflection based on an area of the CMI Code of Conduct and Practice. Students may use reflective frameworks such as Gibbs, Kolb, Rolfe or Burton and explain how the selected professional principle applies to their current or future career. Entrepreneurial Practice Assign… Overall, the assessment integrates strategic analysis, leadership, entrepreneurship, venture development, funding, risk management, professional communication and reflective practice. Overview word count: approximately 360 words. AI-use note: the assignment is classified as AI Amber. AI may be used only within the permitted support categories, and students must disclose which AI tools were used and briefly explain how they were used. Entrepreneurial Practice Assign… Important for your public Reference Library: the brief explicitly states that the document and its case-study materials must not be passed to third parties or posted on any website or social-media platform. Therefore, do not upload this assessment brief itself publicly. Only publish the finished student work if you have the right to do so and it does not reproduce restricted case-study material. Entrepreneurial Practice Assign… Entrepreneurial Practice Assign…

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Strategic Management / Sustainability / Responsible Leadership 2,500 words

Organisational Strategy and Sustainability: Strategic Evaluation of Engineers & Planners Company Ltd

This Consultancy Project Proposal assessment requires students to develop a professional and feasible research proposal addressing a current organisational issue or business challenge affecting an existing organisation. The work combines critical business analysis with research design, secondary-data methodology, ethics and visual communication through an accompanying one-page digital poster. MSc Management Summative Assess… The first task requires students to introduce the selected organisation and critically examine between one and three current challenges. The discussion must be evidence-based and supported by recent sources. Stronger work should connect the identified issues to current affairs, recent news, Sustainable Development Goals and relevant academic or company evidence. MSc Management Summative Assess… The second task requires development of a clear research aim, three objectives and, for stronger submissions, one or two research questions. Students must demonstrate awareness and application of research methodology using secondary research only, while incorporating both qualitative and quantitative approaches. The research design should be directly connected to the selected organisational challenges. MSc Management Summative Assess… The third task focuses on the research plan and ethical considerations. Students must explain ethical issues associated with secondary-data collection and support the discussion using credible literature. The accompanying poster should present a coherent research plan and demonstrate effective data-analysis and data-presentation skills through relevant graphs, charts, tables or descriptive statistics. MSc Management Summative Assess… The fourth task assesses the student's ability to critically organise and synthesise information into a coherent proposal. The written report should use recent, credible sources, while the poster should include a short reflection on challenges encountered when synthesising evidence for the proposed study. MSc Management Summative Assess… The report must be written in the third person and use Harvard referencing. The proposed structure allocates approximately 150 words to the introduction, 400 words to the challenge discussion, 150 words to the research aim and objectives, 500 words to methodology, 200 words to ethical considerations and 100 words to the conclusion. The digital poster has no formal word count but must fit on a single A4 page and use a readable 10–12 point font. MSc Management Summative Assess… MSc Management Summative Assess… Overall, the assessment develops skills in consultancy problem definition, research design, secondary-data analysis, mixed-method thinking, ethical research practice, critical synthesis and professional visual communication.

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Business Consultancy Project: Strategic Analysis, Stakeholder Evaluation and Evidence-Based Recommendations

Business Consultancy, Strategic Management, Business Analysis, Consultancy Project, Stakeholder Analysis, Mendelow Matrix, Business Strategy, Data Analysis, Secondary Research, SWOT Analysis, PESTLE Analysis, Porter’s Five Forces, Balanced Scorecard, Ethics, Sustainability, UN Sustainable Development Goals, Recommendations, Risk Analysis, Implementation Barriers, Organisational Strategy, Business Problem Solving, Employability Skills, Professional Development, Reflective Practice, Project Management, Evidence-Based Decision-Making

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International Human Resource Management / International Business 800 words

Comparative Analysis of Cultural Factors Shaping Human Resource Staffing Strategies in International Enterprises

This individual international human resource management assessment examines how cultural and institutional differences influence recruitment and staffing decisions in international enterprises. Students take the role of an HR representative for VetDopomoga, a Ukraine-based international veterinary clinic chain planning to expand into either the United Kingdom or India. The final output is a concise academic poster of up to two pages and approximately 800 words ±10%, supported by appropriate visual material. Assignment 1_The Comparative An… The first component requires comparison of the United Kingdom and India with Ukraine. Students examine relevant cultural characteristics, including communication style, hierarchy and power distance, individualism versus collectivism and approaches to time, alongside institutional factors such as labour-market conditions and employment or regulatory environments. This comparison provides the contextual basis for evaluating how recruitment practices may need to change across markets. Assignment 1_The Comparative An… Students must then apply an appropriate international HR staffing strategy, choosing from ethnocentric, polycentric, regiocentric or geocentric approaches. Based on their analysis, they must recommend which market VetDopomoga should enter first and which should follow, providing clear evidence-based justification. Assignment 1_The Comparative An… A central theoretical component requires application of one cultural framework, selected from the Cultural Intelligence framework, Erin Meyer’s Culture Map, the GLOBE Project or Hofstede’s Cultural Dimensions Theory. Students focus on two dimensions from their selected framework and use them to evaluate the benefits and challenges associated with recruitment practices in Ukraine, the United Kingdom and India. Assignment 1_The Comparative An… The poster must also examine a recent cultural, economic or political event affecting the three national contexts and explain its implications for international recruitment and staffing. Examples suggested in the brief include changing social attitudes following COVID-19, economic shifts affecting demand for specialist labour and post-Brexit employment or migration policies. Assignment 1_The Comparative An… Students additionally research best-practice recruitment examples from international veterinary enterprises operating in the UK and India and identify practices VetDopomoga could adopt or adapt in each market. The final recommendation must identify the preferred first expansion destination and provide three evidence-based reasons supporting the decision. Assignment 1_The Comparative An… Assessment criteria place strong emphasis on content and findings, theoretical application, critical analysis, source quality and Harvard referencing, as well as poster presentation and structure. High-quality work is expected to go beyond description by applying cultural theory directly to HRM practices and critically evaluating the implications of cultural and institutional differences for international recruitment decisions. Assignment 1_The Comparative An… Assignment 1_The Comparative An…

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Cyber Security / Internet of Things / Connected Systems 4,500 words

Security Evaluation for Connected Systems: IoT Strategy, Secure Design, Security Auditing and Organisational Change

This Security of Connected Systems assessment requires students to act as an external IoT Security and Scaling Strategist for a rapidly expanding Coventry-based technology startup specialising in connected devices and smart energy-monitoring systems. The client intends to scale its operations and enter new markets and therefore requires both organisational-change guidance and a comprehensive evaluation of its cybersecurity posture. 38f2fba9a933f212c9e46e8cc591cf2… The report combines business strategy with technical cybersecurity analysis. Students must review different secure design and development methodologies, compare their strengths and weaknesses, and recommend an appropriate approach for integrating security into the client's IoT software-development lifecycle. 38f2fba9a933f212c9e46e8cc591cf2… 38f2fba9a933f212c9e46e8cc591cf2… A major component of the assessment focuses on organisational change strategy. Students examine the internal and external factors driving organisational growth, develop a comprehensive strategy for achieving the client's business objectives, and explain how that strategy should be implemented and monitored. The report must also critically evaluate relevant change-management theories and models and address the complexities of leading and managing strategic transformation. This section carries 35% of the marks and is allocated approximately 2,000 words. 38f2fba9a933f212c9e46e8cc591cf2… The Security Audit Strategy section requires students to design a guide for auditing the client's connected system. Different approaches, including methodologies such as PTES and OWASP, should be compared and evaluated. Students must explain each stage of the selected testing methodology and justify why the individual steps are required. 38f2fba9a933f212c9e46e8cc591cf2… The final technical component applies these principles to an IoT vulnerability case study. Students research a real vulnerability in an IoT device, explain where the security flaw was introduced, identify weaknesses in the secure-design or audit process, assess the resulting security impact and propose appropriate corrective actions. 38f2fba9a933f212c9e46e8cc591cf2… Overall, the coursework integrates IoT cybersecurity, secure software development, security auditing, vulnerability analysis, organisational strategy and strategic change management. The marking scheme allocates 35% to organisational-change strategy, 20% each to secure design and development, security auditing and security recommendations, and 5% to report structure. 38f2fba9a933f212c9e46e8cc591cf2… Important: the brief states that it is for Coventry University Group students' own use and must not be passed to third parties or posted on a website. 38f2fba9a933f212c9e46e8cc591cf2… So use an original public summary like the one above, but do not upload the original brief itself.

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4,200 words

Global Supply Chain Strategy for the Gatwick Airport Northern Runway Expansion

This individual Global Supply Chain Management assessment requires students to prepare a professional strategic report on the supply chain implications of the Gatwick Airport Northern Runway expansion. The task focuses on applying contemporary supply chain theories, models and analytical techniques to a complex infrastructure development context, with particular attention to strategic relationships, operational efficiency, risk and resilience. Assignment Brief 2 - MBA013 Glo… The report begins by establishing the background to the organisation and examining its current global supply chain context. Students are expected to consider issues including strategic supplier and customer relationships, risk management, resilience, outsourcing, supplier planning and selection, integration, supply chain networks, leadership, benchmarking, decision-making, lean principles and agile supply chains. These areas provide the basis for evaluating how supply chain performance can be improved in a major airport expansion project. Assignment Brief 2 - MBA013 Glo… A key analytical component requires a PESTEL analysis to critically assess how external political, economic, social, technological, environmental and legal factors may affect the organisation’s global supply chain. The purpose is not only to identify external pressures but to evaluate how those factors may influence sourcing, supplier management, cost, risk exposure, resilience and long-term strategic decision-making. Assignment Brief 2 - MBA013 Glo… The final part of the report develops strategic recommendations aimed at optimising supply chain performance. Recommendations should focus on reducing costs, supporting sustainability, improving operational efficiency and strengthening resilience. Students are expected to justify these proposals through explicit application of relevant theories and models such as lean supply chain, agile supply chain and global sourcing strategies, supported by appropriate academic and practical evidence. Assignment Brief 2 - MBA013 Glo… The marking criteria place substantial emphasis on theoretical application, critical analysis and the connection between theory and practice. The rubric allocates 25% to theory and frameworks, 30% to analysis and evaluation, 20% to conclusions and recommendations, and 25% to structure, presentation and referencing. Assignment Brief 2 - MBA013 Glo… Assignment Brief 2 - MBA013 Glo… Overall, the assessment develops competence in strategic supply chain analysis, infrastructure logistics, risk and resilience, supplier management, lean and agile operations, sustainability and evidence-based recommendation development. Overview word count: approximately 350 words. Important: the brief explicitly states that the report must be original and that students should not use AI to produce the work. Assignment Brief 2 - MBA013 Glo…

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Business Management / Consultancy / Strategic Management 5,000 words

Business Consultancy Project: Strategic Analysis, Stakeholder Evaluation and Evidence-Based Recommendations

This Business Consultancy Project assessment requires students to produce a professional 5,000-word consultancy report addressing a strategically important issue, challenge or problem facing a client organisation. The project must normally continue from the topic and client proposed in the earlier Consultancy Project Proposal, ensuring continuity between the proposal and final consultancy work. The assessment is designed to replicate professional consultancy practice through independent research, critical analysis and the development of actionable recommendations. Copy of Apr 25 Onwards brief_EE… Copy of Apr 25 Onwards brief_EE… The report begins with an Executive Summary, followed by an introduction and company/client overview. Students must define one clear business problem, establish the overall project aim and purpose, and specify the consultancy focus, which may relate to areas such as strategy, human resources, marketing or sustainability. The selected issue should be clearly connected to the organisation’s wider strategic and industry context. Copy of Apr 25 Onwards brief_EE… A dedicated Stakeholder Analysis section requires identification and evaluation of internal and external stakeholders. Students must assess stakeholder interests, influence, expectations, conflicts and power relationships, and are encouraged to apply a framework such as Mendelow’s Matrix. The purpose is to show how stakeholder dynamics influence the consultancy problem and the feasibility of proposed solutions. Copy of Apr 25 Onwards brief_EE… The largest section is Data Analysis and Framework Application, where students critically evaluate secondary evidence and apply two or three relevant management frameworks. Suitable approaches may include SWOT, PESTLE, Porter’s frameworks and the Balanced Scorecard. The analysis should incorporate credible company and industry evidence, Excel outputs, tables or charts where relevant, and connect patterns in the data to strategic, operational or HR implications. Ethical and sustainability considerations should be embedded where appropriate. Copy of Apr 25 Onwards brief_EE… The project concludes with three prioritised and evidence-based recommendations. Recommendations should be practical, justified, risk-aware and linked directly to the findings. Students must explain expected benefits and demonstrate how the proposed actions create strategic value for the client organisation. Copy of Apr 25 Onwards brief_EE… The final assessed section is a 500-word Employability Reflection covering skills developed through the project, application of theory to practice, professional behaviours, personal strengths and weaknesses, career relevance and specific future-development actions. Copy of Apr 25 Onwards brief_EE… Overall, the assessment integrates consultancy problem definition, stakeholder analysis, strategic frameworks, secondary-data interpretation, ethics, sustainability, recommendations and professional reflection within a Masters-level business project. The marking criteria reward criticality, current evidence, intellectual originality, professional consultancy thinking and accurate Harvard referencing. Copy of Apr 25 Onwards brief_EE… One important point: the brief states that the majority of references should come from sources published within the last 6–12 months, so the final project is expected to use very current company, industry and academic evidence. Copy of Apr 25 Onwards brief_EE…

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Data Science / Time Series Analysis / Machine Learning

Time Series Modelling Case Study: Oil Price Forecasting with ARMA and Alternative Models

This Time Series Modelling Case Study requires students to analyse real-world oil-price time-series data and develop forecasting models capable of predicting future values. The assessment combines traditional statistical time-series techniques with an alternative forecasting approach, requiring students to demonstrate practical modelling skills, critical research engagement and evidence-based interpretation of forecasting results. The coursework is completed individually and contributes 40% of the assessment. assing,,, (1) The assessment is divided into three main parts. Part 1 focuses on developing an ARMA-based forecasting model using daily oil-price data covering approximately 2024 to 2026. Students begin with exploratory data analysis and initial visualisation before testing whether the time series is stationary. Where necessary, appropriate transformations or differencing must be applied to obtain stationarity. Students then define an ARMA model and identify suitable p, d and q parameters using an AIC-based model-selection procedure across the parameter ranges specified in the brief. assing,,, (1) Model adequacy must be assessed using diagnostic analysis. Students inspect residuals, generate additional ACF plots, examine residual distributions and evaluate prediction performance using appropriate metrics such as RMSE. The selected model is then used to forecast oil prices 24 months into the future, with appropriate confidence intervals added to communicate forecast uncertainty. assing,,, (1) Part 2 requires students to research and implement an alternative forecasting approach. Suggested examples include LSTM and Prophet, although another appropriate model may be proposed. Students conduct a literature review supporting the alternative method, build and where relevant hyperparameter-tune the model, generate another 24-month forecast, visualise predictions and confidence intervals, and calculate suitable evaluation metrics. This component is intended to demonstrate independent research and the ability to propose an alternative solution rather than relying only on the conventional ARMA approach. assing,,, (1) Part 3 consists of a 6–8 page technical report explaining the modelling process, forecasting results and resulting inferences. The report should provide a critical analysis rather than simply reproducing numerical outputs. Students are expected to explain why results occurred, justify modelling choices, evaluate how those choices influenced performance, compare forecasts with subsequently observed real data where possible, and construct a coherent narrative supported by plots, images, summary statistics and academic literature. Future improvements to the modelling approach should also be critically discussed. assing,,, (1) Submission consists of both the report and working code. The code may be submitted directly or through an accessible Colab or GitHub repository and must reproduce all models, figures and numerical results presented in the report. The assessment allocates 60% of the marks to code and 40% to the report. Within the coding component, modelling and forecasting completion accounts for 40 marks and code quality and annotation for 20 marks. The report is assessed on analysis and inference, methodological justification, comparison of the two modelling approaches, presentation quality, figures and use of appropriate references. assing,,, (1) Key technical expectations include appropriate testing for stationarity, use of methods such as ADF, ACF, PACF and differencing, systematic model selection, forecasting, evaluation and clear comparison between the traditional ARMA model and the chosen alternative approach. Higher-quality work is expected to interpret what the forecasts mean, identify potential improvements and demonstrate sound technical communication rather than merely reporting model outputs. assing,,, (1) Important for the public Reference Library: the brief explicitly states that students must not use generative AI to write the report, and the rubric indicates that AI text-generation use may result in zero marks for the whole assignment. Therefore, the public entry should remain a high-level description of the assessment rather than material intended for direct submission. assing,,, (1)

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Supply Chain Operations and Logistics Management 3,000 words

Critical Review of Global Logistics: Supply Chain Strategy, Resilience and Sustainability

This postgraduate logistics assessment requires students to conduct a critical review of the global logistics operations and strategies of a selected multinational manufacturing organisation. The chosen company must operate internationally and have sufficient publicly available information to support detailed academic and industry research. The report examines how global manufacturers structure, manage and improve their upstream and downstream logistics channels in increasingly complex and uncertain supply-chain environments. Component_2_NBS_7054A_25_Report… The first part analyses the organisation’s upstream and downstream logistics channels and evaluates the logistics strategies it has adopted. Particular attention is given to how the organisation responded to disruption caused by the COVID-19 pandemic. Students examine how supply-chain networks were reconfigured and how logistics strategies were adapted to maintain operations, while explicitly relating these responses to relevant performance objectives and supply-chain dimensions. Component_2_NBS_7054A_25_Report… The second part focuses on value creation within global logistics networks. Students evaluate how supply-chain intermediaries contribute to value co-creation while balancing operational costs and reducing waste or Muda. The analysis also considers how communication and information sharing support the objectives of the organisation’s marketing channel network and identifies lessons learned from pandemic-related disruption. Component_2_NBS_7054A_25_Report… The final section examines how the organisation can strengthen the sustainability of its logistics operations. Students assess the feasibility of aligning circular economy principles and Industry 4.0 technologies with existing inbound and outbound logistics activities. Relevant issues include reduced material use, reuse, repair, refurbishment, alternative transport modes, carbon-footprint reduction and environmental efficiency. Students must also recommend operational decisions that apply innovation-led lean approaches to sustainability initiatives. Component_2_NBS_7054A_25_Report… The marking criteria place 25% of the assessment on logistics theories and strategies, 35% on value co-creation, communication and resilient logistics networks, and 40% on circular economy, Industry 4.0 and sustainability recommendations. Marking_Criteria_NBS_7054A_25_R… Overall, the assessment integrates global logistics strategy, resilience, lean operations, digitalisation, sustainability and evidence-based supply-chain decision-making within a real organisational case study. Overview word count: approximately 340 words.

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Computer Science / Algorithms / Network Optimisation

An Improved Dijkstra’s Shortest Path Algorithm for Sparse Networks

This technical research paper investigates an improved version of Dijkstra’s shortest path algorithm for sparse weighted networks. Traditional implementations of Dijkstra’s algorithm can achieve a time complexity of O(m + n log n) when Fibonacci heaps are used, but the authors argue that heap construction increases implementation complexity. The proposed approach modifies the original algorithm so that heap construction is avoided while maintaining competitive performance on sparse graphs. An_improved_Dijkstra’s_shortest… The study focuses on the single-source shortest path problem in weighted directed graphs with non-negative edge lengths. It begins by reviewing a refined Dijkstra algorithm in which each vertex maintains a distance label representing an upper bound on the shortest distance from the source vertex. The main computational bottleneck is repeatedly identifying the unvisited vertex with the smallest distance label. A naïve implementation requires O(n²) time, while Fibonacci-heap implementations improve efficiency but introduce additional implementation complexity. An_improved_Dijkstra’s_shortest… An_improved_Dijkstra’s_shortest… The authors propose an improved Dijkstra algorithm that maintains distance labels in an ordered list. When a distance label changes, the corresponding entry is reinserted into the appropriate location rather than rebuilding or maintaining a heap. The algorithm exploits the characteristics of sparse networks, where each vertex is connected to only a relatively small number of edges. This is particularly relevant to road networks, where the maximum degree of each node is typically low. An_improved_Dijkstra’s_shortest… To support efficient reinsertion, the paper introduces a predefined step-size vector and a binary-search-style process for locating the correct insertion position. This approach reduces the number of comparisons required while avoiding the division operations commonly associated with standard binary search implementations. An_improved_Dijkstra’s_shortest… An_improved_Dijkstra’s_shortest… The theoretical analysis shows that the proposed method requires approximately O(m + Dmax log(n!)) comparisons and arithmetic operations, where m represents the number of edges and Dmax is the maximum number of edges incident on a vertex. The authors argue that this complexity makes the approach especially suitable for large-scale sparse networks where the maximum node degree remains relatively small. An_improved_Dijkstra’s_shortest… An_improved_Dijkstra’s_shortest… The algorithm is evaluated through numerical experiments implemented in MATLAB. Two families of randomly generated sparse networks are tested, with network sizes ranging from approximately 10,000 to 21,000 nodes. The first experiment uses a maximum node degree of four, while the second uses a maximum degree of six. Experimental ratios reported in the paper remain close to the theoretical complexity estimate as network size increases. An_improved_Dijkstra’s_shortest… The paper concludes that the improved Dijkstra approach is practical for large sparse networks, particularly road-traffic networks. By avoiding Fibonacci-heap construction and using an ordered-list reinsertion strategy, the algorithm aims to simplify implementation while maintaining competitive computational performance for shortest-path calculations. An_improved_Dijkstra’s_shortest… Important: because this is a published journal article rather than a university assignment brief, fields such as module name, assessment level and assignment word count are not stated in the source. For the portal, it is safer to use Not specified / Not applicable for those fields rather than inventing academic-assessment details.

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Digital Transformation / Management and Leadership 1,500 words

Leading Through Digital Change: Digital Transformation Strategy, Emerging Technologies and Leadership

This postgraduate assessment requires students to act as a Digital Transformation Consultant and evaluate how a selected organisation should respond to accelerating technological change. Students choose one organisation from the options provided in the brief and prepare a Digital Transformation Report and accompanying poster designed to recommend changes that can help the organisation maintain competitive advantage and create business value. Summative_Assessment_Leading_Th… The first section focuses on a Digital Transformation Strategic Framework. Students must critically review and apply one recognised framework, choosing from the McKinsey 4Ds, BCG 3 Stages, Gartner’s 6 Steps or Cognizant’s 4 Pillars. The analysis should identify appropriate digital-transformation objectives and explain how these can support business functions such as operations, ICT and marketing. Higher-level work is expected to move beyond description and critically evaluate recent digital initiatives and organisational challenges. Summative_Assessment_Leading_Th… The second component is an A4 poster examining future digital trends. Students must evaluate two disruptive technologies or techniques likely to influence the relevant industry, employment and the labour market over the next five years. Suggested technologies include artificial intelligence and machine learning, 5G connectivity, IoT, robotics, drone delivery, blockchain, augmented reality and virtual reality. Academic literature and real-world examples are expected to support the evaluation. Summative_Assessment_Leading_Th… The third section addresses Digital Leadership. Students analyse and recommend two leadership styles that could support organisational transformation. Relevant approaches may include hyperaware agile leadership, ethical-tech leadership, people-oriented leadership, agile leadership and Goleman’s leadership styles. The analysis should explain how leadership capabilities can support collaboration, organisational networks and people during digital change. Summative_Assessment_Leading_Th… The final submission should contain a clear introduction, conclusion and Harvard-referenced evidence, and must be written in the third person with professional academic presentation. Summative_Assessment_Leading_Th… Overview word count: approximately 330 words.

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Cyber Security / Digital Forensics 3,877 words

Digital Forensics Investigation: USB, Memory and Windows Registry Analysis

This Digital Forensics Investigation Report presents a multi-source forensic examination involving removable media, volatile memory and a Windows disk image. The work is undertaken within an MSc Cyber Security context and demonstrates the application of forensic procedures, specialist analysis tools and evidential reasoning to investigate suspected criminal and malicious activity. The report places particular emphasis on maintaining evidence integrity, reconstructing activity across different forensic sources and correlating artefacts to produce defensible investigative findings. DF_Report_Sathiyaprakash The first part investigates a FAT32 USB forensic image associated with suspected video piracy and other potentially criminal activity. The examination uses tools including FTK Imager, Autopsy, Sleuth Kit, ewfmount, cryptographic hashing utilities and VeraCrypt. The methodology includes pre- and post-examination hash verification, read-only mounting, filesystem enumeration, deleted-file analysis and low-level sector examination. The investigation identifies deleted artefacts, portable anti-forensic utilities, browser evidence and an encrypted VeraCrypt container concealed within unallocated disk space. DF_Report_Sathiyaprakash The USB investigation also demonstrates the importance of evidence integrity and chain of custody. MD5 and SHA-256 hashes are used to establish and later confirm the integrity of forensic copies, while analysis is conducted without modifying the original evidence. The report examines filesystem structures, deleted files, anti-forensic tooling and encrypted data and records evidence handling through a formal chain-of-custody process. DF_Report_Sathiyaprakash DF_Report_Sathiyaprakash The second part focuses on volatile-memory forensics using a Windows memory image. Volatility 3 is used to identify the operating-system profile, reconstruct process hierarchies, inspect process ownership and security identifiers, and extract suspicious process memory. Particular attention is given to AtomicService.exe, which is observed running with SYSTEM privileges and associated with the Atomic Red Team framework and MITRE ATT&CK technique T1543.003 – Windows Service. The investigation also considers PowerShell activity, process execution timelines and indicators of suspicious behaviour. DF_Report_Sathiyaprakash DF_Report_Sathiyaprakash The third part conducts Windows Registry forensic analysis on the WinRegEvidenceP3.vhd image. Registry artefacts are examined using RegRipper, with analysis covering SYSTEM, SOFTWARE, SAM and NTUSER.DAT hives. The investigation evaluates system configuration, user accounts, application execution and persistence evidence using artefacts such as Run keys, BAM, Prefetch and scheduled tasks. These findings are then correlated with evidence recovered from volatile memory to reconstruct the sequence of suspicious activity. DF_Report_Sathiyaprakash Across the report, evidence from disk, memory and the Windows Registry is combined to reconstruct malicious activity and identify persistence mechanisms, elevated processes, suspicious user accounts and adversary-simulation tools. The analysis maps relevant behaviour to the MITRE ATT&CK framework and considers both technical findings and their evidential significance. The report therefore demonstrates practical competence in forensic acquisition principles, artefact analysis, timeline reconstruction, malware and process investigation, evidence correlation and professional reporting. Important for the Reference Library: this upload contains an actual student name on the cover page and detailed case evidence. Since your Reference Library says there is no student record behind uploaded past work, I would use the generic title and overview above rather than copying the student-identifying cover-page information into the public metadata. DF_Report_Sathiyaprakash

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Computer Science / Algorithms / Computational Complexity

Modified Merge Sort for Large-Scale Data: Algorithm Analysis, Complexity and Evaluation

This Computational Algorithms and Paradigms assignment critically examines a modified merge sort algorithm designed for large-scale datasets. The work focuses on the computational problem of sorting very large collections of data efficiently while preserving the stability and predictable complexity associated with classical merge sort. The analysed approach replaces recursive processing with an iterative successive-merging strategy intended to reduce stack overhead and improve practical performance on large datasets. Dubba ramesh(up) The first section identifies the underlying computational problem and frames the main research questions. These include how standard merge sort can be modified to improve large-scale performance, whether recursion can be replaced with a non-recursive iterative process, whether the proposed double-merge technique reduces resource consumption, and how its computational performance compares with classical merge sort. Dubba ramesh(up) A technical section then reconstructs the algorithm in pseudocode. The modified process begins with subsequences of size one and repeatedly merges adjacent sorted subsequences, doubling the merge size after each iteration until the entire dataset is sorted. This bottom-up approach removes the recursive decomposition used in conventional merge sort. Dubba ramesh(up) The assignment also identifies the algorithm's principal inputs and outputs. Inputs include the dataset, number of elements, subsequence boundaries and temporary storage required during merging. The resulting output is a fully sorted and stable sequence. Dubba ramesh(up) Complexity analysis shows that the modified algorithm processes approximately n elements across log₂(n) merging levels, resulting in O(n log n) time complexity in both best and worst cases. Because an auxiliary array is used during merging, the reported space complexity is O(n). Dubba ramesh(up) The final critical evaluation highlights the main benefits of the modified approach, including removal of recursive-call overhead, greater stability when processing very large datasets, predictable performance and preservation of merge-sort stability. Its main limitation is the continued requirement for auxiliary memory during the merge operation. The work also notes that the performance advantages are most relevant for large-scale datasets and may be less significant for smaller inputs. Dubba ramesh(up) Overall, the assignment integrates algorithm interpretation, pseudocode extraction, input-output analysis, complexity analysis and critical evaluation within the context of large-scale sorting. Note: this upload appears to be the completed student response rather than the original assessment brief, so the referencing style and exact formal overall word limit are not stated. I would leave the reference-style field as Not specified unless you also upload the official 7COM1078 guideline.

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Artificial Intelligence / International Business 3,000 words

AI Innovation Consultancy: Evaluating Artificial Intelligence Solutions for Business Problems

This individual consultancy assessment requires students to act as an AI Innovation Consultant and evaluate how artificial intelligence could address a significant real-world business problem. Students select one industry—such as healthcare, retail, FinTech, manufacturing or agriculture—and concentrate on a single clearly defined organisational challenge rather than comparing multiple sectors. Potential issues include long waiting times, high operating costs, fraud and risk, poor customer experience or inefficient supply chains. The report develops a practical AI solution by identifying suitable technologies such as machine learning, natural language processing or computer vision and explaining how they would operate within the chosen organisational context. Students are not required to build an AI system; instead, the emphasis is on demonstrating business-level technical understanding, critical thinking and the ability to assess whether the proposed technology can realistically integrate with existing organisational processes. The analysis considers the capabilities and limitations of AI, technical feasibility, integration requirements and the skills or organisational capabilities required for implementation. Students must also critically examine ethical, legal and social implications, including issues such as algorithmic bias, transparency, accountability, privacy and regulatory obligations such as UK GDPR. Appropriate risk-mitigation measures should be proposed. A substantial element of the report develops the business case for AI adoption. Students evaluate implementation costs and expected benefits, estimate return on investment, identify assumptions and commercial risks, and assess the overall strategic value of the solution to the organisation. The report concludes with clear recommendations, implementation priorities and a final judgement on whether the proposed AI initiative is feasible and worthwhile. The assessment places strong emphasis on critical analysis, technical understanding, business acumen and professional communication. Students are expected to support arguments with credible academic, industry and government evidence and include at least two professional visualisations such as frameworks, diagrams or tables. Harvard referencing is required throughout. Overview word count: approximately 330 words. The brief also allows authorised use of generative AI for idea generation, drafting/structuring and proofreading, provided the student verifies accuracy, references appropriately and submits the required GenAI declaration.

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Probability and Statistics / Data Analysis / Python

Probability and Statistics Jigsaw Puzzle: Probability Calculations and Chi-Square Analysis in Python

This technical Probability and Statistics exercise presents a set of Python code fragments designed to demonstrate basic probability calculations and statistical hypothesis testing. The material is organised as a jigsaw-style collection of code segments, allowing the underlying logical sequence to be reconstructed from variable definitions, probability calculations, observed data, statistical testing and final interpretation. Jigsaw_Puzzle_3_Original_Struct… The first part models a two-bag probability problem. Bag 1 contains four white and two black items, while Bag 2 contains three white and five black items. The code calculates the probabilities of selecting a white or black item from each bag and then uses multiplication rules to determine the probability of drawing two white items, two black items, or one white and one black item across the two bags. Jigsaw_Puzzle_3_Original_Struct… Jigsaw_Puzzle_3_Original_Struct… Jigsaw_Puzzle_3_Original_Struct… A second section demonstrates a chi-square test of independence using an observed frequency table containing grade outcomes for girls and boys across grades A, B, C and D. The data are stored in a NumPy array and analysed using SciPy's chi2_contingency function. The resulting chi-square statistic, p-value, degrees of freedom and expected frequencies are calculated and displayed. Jigsaw_Puzzle_3_Original_Struct… Jigsaw_Puzzle_3_Original_Struct… The final fragment applies a conventional significance threshold of α = 0.05. If the p-value is greater than 0.05, the code reports that the null hypothesis should not be rejected; otherwise, it concludes that a statistically significant difference exists. Jigsaw_Puzzle_3_Original_Struct… Overall, the document demonstrates core statistical-programming concepts including probability rules, contingency tables, chi-square analysis, expected frequencies, p-value interpretation and hypothesis testing using Python, NumPy and SciPy. Important: because this file does not identify a university, module, academic level, academic year, assignment brief, formal word count or referencing system, I would leave those fields as Not specified rather than guessing.

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Cyber Security / Applied Cryptography / Secure Systems Design 2,500 words

Secure Property Contract Exchange: Cryptographic Protocol Design, Threat Modelling and Post-Quantum Readiness

This Applied Theory of Cyber Security and Secure Design coursework places students in the role of a cyber security consultant engaged by Hackit & Run LLP, a legal firm specialising in UK and international property transactions. The firm wishes to implement a secure digital system for handling, exchanging and legally signing property contracts. Students must design and evaluate a secure communication protocol supporting interactions between the buyer’s solicitor, the seller’s solicitor and the buyer while addressing both first-time communications and previously established secure relationships. 11b17febb9eeb4570f76f6ca95a831a… Section A – Cryptographic Protocol Design, worth 45%, requires a complete secure communication protocol. Students must explain how trust is initially established, how later communications can be simplified without weakening confidentiality, integrity or availability, and how the buyer can digitally sign a contract in a manner enforceable under UK law. The design must justify specific cryptographic algorithms for functions such as key exchange, bulk encryption, digital signatures and hashing. The protocol must be presented through both a sequence diagram showing message flows and cryptographic operations and pseudocode explaining the key algorithmic stages. 11b17febb9eeb4570f76f6ca95a831a… Section B – Threat Modelling, worth 20%, requires a focused analysis using the STRIDE methodology. Students identify three realistic threats from different STRIDE categories and analyse the attack vector, asset at risk and potential effect on the legal transaction. Each threat must then be connected back to specific protocol defences, with residual risks acknowledged where controls cannot provide complete mitigation. The guidance encourages consideration of issues such as social engineering, insider threats, key-management failures and availability risks in addition to purely cryptographic attacks. 11b17febb9eeb4570f76f6ca95a831a… Section C – Security Evaluation Against Standards, worth 15%, requires students to evaluate the proposed system against a recognised cybersecurity standard or framework. Options include ISO/IEC 27001:2022, Common Criteria (ISO/IEC 15408) and the OWASP Application Security Verification Standard. Students select three or four directly relevant controls or requirements, assess whether the proposed design satisfies them, identify gaps and recommend specific improvements. 11b17febb9eeb4570f76f6ca95a831a… Section D – Post-Quantum Readiness and Critical Reflection, worth 15%, examines how a future quantum-capable adversary could affect the protocol. Students identify vulnerable cryptographic components, discuss the NIST Post-Quantum Cryptography standardisation programme, and examine replacement algorithms such as ML-KEM for key establishment and ML-DSA for digital signatures. They must also evaluate a hybrid migration strategy combining classical and post-quantum algorithms, considering performance overhead, backward compatibility and the legal admissibility of post-quantum digital signatures. 11b17febb9eeb4570f76f6ca95a831a… The remaining 5% evaluates professional report quality, logical structure, technical language, integration of diagrams and consistent CUHarvard referencing. Higher-quality work is expected to demonstrate a sophisticated trust model, clear traceability between threats and controls, precise standards mapping, practical security recommendations and well-evidenced analysis of post-quantum migration. 11b17febb9eeb4570f76f6ca95a831a… Important for the public Reference Library: the brief states that the assessment document is intended only for Coventry University Group students and must not be passed to third parties or posted on any website. Therefore, publish only an original high-level description such as the overview above; do not upload or reproduce the original assignment brief publicly. 11b17febb9eeb4570f76f6ca95a831a…

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3,000 words

ParkaLot Enterprise Parking Garage Management System: Software Analysis, Design and Prototype Development

This enterprise software engineering project requires students to analyse, design and prototype a centralised parking garage management system for ParkaLot Group, a UK operator of multi-storey parking facilities. The existing organisation relies heavily on manual processes, local spreadsheets and simple barrier-based vehicle counts, resulting in limited real-time occupancy information, inconsistent reservation arrangements, decentralised billing and reduced ability to optimise parking capacity and revenue. COMP1471 CW 2526 (1) The proposed system supports ParkaLot’s wider digital transformation by integrating customer registration, reservations, parking-space allocation, occupancy monitoring, contracts and billing. Customers can check availability and reserve parking through an online portal, while frequent and corporate users can establish recurring arrangements or block reservations. License-plate recognition and individual parking-space sensors enable automated access control and real-time occupancy tracking. COMP1471 CW 2526 (1) Additional functionality includes centralised electronic billing, dynamic pricing, promotional schemes and predictive decision-making for controlled overbooking. Historical usage data may be analysed to estimate no-shows, early departures and overstays, while operational dashboards support staffing, pricing and capacity-management decisions across the garage network. COMP1471 CW 2526 (1) Development is undertaken in two phases. The first uses structured analysis and design, requiring an Entity Relationship Diagram, Data Flow Diagram including a context diagram, and implementation of a prototype database. The second expands the solution using object-oriented analysis and UML, with emphasis on adaptable and reusable software design. COMP1471 CW 2526 (1) The final report covers the software-engineering **5 Ps—Problem, Process, Project, Product and People—**alongside ERD and DFD models, UML use cases, at least three sequence diagrams, a detailed class diagram and application of design patterns such as GRASP. Students must also submit prototype evidence, source code, personal reflection, peer assessment and work-contribution documentation. COMP1471 CW 2526 (1) Overall, the assessment integrates requirements engineering, structured modelling, object-oriented design, database development, design patterns, software project management, implementation and acceptance testing within a realistic enterprise-system case study. Overview word count: approximately 360 words. AI-use note: the brief permits Levels 1–4 of generative-AI use, including research and exploration at Level 4, but all final submitted text, code, diagrams and designs must be the students’ own work. Level 4 use requires disclosure, an appendix of prompts/outputs and reflective commentary. COMP1471 CW 2526 (1)

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Data Science / Artificial Intelligence / Generative Modelling

Generative Modelling Case Study: GANs for Medical Imaging, Cybersecurity and Creative AI

This Generative Modelling Case Study requires students to design, implement and evaluate Generative Adversarial Networks (GANs) across a range of synthetic and real-world applications. The coursework develops both theoretical understanding and practical deep-learning skills, with emphasis on building models, evaluating generated data and critically interpreting model performance. The assessment addresses research understanding, originality, future development and scholarly communication in data science. Generative modelling case study… Part 1 – Building and Understanding GANs from Scratch focuses on fundamental GAN concepts using synthetic two-dimensional data. Students first reproduce a sine-wave GAN from the tutorial and then create a second synthetic distribution using either a 2D spiral, a mixture of Gaussians or a noisy parametric curve. They must modify aspects of the GAN architecture, such as activation functions or network depth, and visually compare generated samples with the original data distribution. Generative modelling case study… Part 2 – Real-World GAN Applications extends the work across three application domains. The first application uses the BloodMNIST subset of MedMNIST to train a DCGAN that generates synthetic blood-cell microscope images. Students explore the dataset, analyse class distributions, train the model, monitor generator and discriminator losses and compare real and generated images using both visual inspection and quantitative measures such as the Fréchet Inception Distance (FID). An optional extension involves implementing a class-conditioned GAN capable of generating images from specific categories. Generative modelling case study… The second application addresses cybersecurity using the CICIDS 2017 intrusion-detection dataset. Students construct a GAN that generates synthetic network-traffic feature vectors rather than images. The model is trained using benign and denial-of-service traffic, and generated samples are compared with real traffic using dimensionality-reduction techniques such as PCA or t-SNE. Students must evaluate how closely the synthetic traffic reflects the distribution of genuine network data. An extension allows analysis of the full CICIDS dataset and evaluation across different attack types. Generative modelling case study… The third application explores Creative AI using the Google QuickDraw pizza category. Students implement another DCGAN to generate artificial pizza sketches, track training behaviour across epochs, and compare generated sketches with genuine examples using both visual inspection and quantitative metrics such as FID. Extension work may examine additional QuickDraw categories and investigate how model performance changes with class and sketch complexity. Generative modelling case study… Submission consists of a 6–8 page report together with working code. The report should explain the analysis undertaken, justify modelling decisions, describe the network architectures, interpret the results and incorporate suitable figures, evaluation metrics and references. The accompanying code must reproduce the figures, models and numerical results reported and must execute successfully when tested. Generative modelling case study… The marking scheme places 60% of the marks on code and 40% on the report. Within the coding component, 40 marks relate to completing the GAN modelling tasks and 20 marks assess code quality, modularity and annotation. The report is assessed on discussion and interpretation of the analysis, justification of architectural choices, results presentation, document quality, figures and appropriate academic references. Generative modelling case study… Important for the public Reference Library: the brief explicitly states that students must not use generative AI to write the report, and the rubric states that AI-generated report text can result in zero marks for the whole assignment. Therefore, use this entry only as a high-level public description of the assessment and do not present generated report content as something students can submit directly. Generative modelling case study… Generative modelling case study…

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Project Management / Professional Development / Business Strategy 5,000 words

Professional Project Portfolio and Strategic Business Presentation

This Level 7 assessment requires students to compile a comprehensive Portfolio of Evidence demonstrating their project contribution, reflective learning, professional skills and career development. The portfolio has a maximum length of 5,000 words and is designed to evidence both technical or disciplinary project engagement and the student’s development as a reflective professional. The assessment is organised into three main components: a Discipline Report, Project Work Logbook, and Career Development Plan. Assessment Overview The Discipline Report, worth 40% of the portfolio, provides an overview of the project and its conclusions, alongside a self-reflection on the student’s project experience. Students also complete a personal skills analysis and provide a confidential summary of their team’s delivery. This section therefore combines project understanding with critical self-evaluation, skills awareness and evaluation of collaborative performance. Assessment Overview The Project Work Logbook, worth 30%, records the student’s activities on a weekly basis. Students summarise the work completed each week and document problems or challenges encountered during the project together with the approaches used to resolve them. The marking criteria emphasise consistency, level of detail, organisation and the ability to identify and address project-related difficulties. Assessment Overview Assessment Overview The Career Development Plan, also worth 30%, requires students to define a realistic future career pathway, identify relevant jobs and organisations, and evaluate the skills and knowledge needed to progress toward those goals. Students must also complete an additional professional-development course, such as CPD or LinkedIn Learning, to demonstrate practical upskilling and continued professional development. Assessment Overview A related team presentation forms a second assessment activity. Teams of four to five students must present face to face for approximately 10–15 minutes to a small management-board audience. All team members are expected to contribute approximately equal content and speaking time, with provision for questions and answers. The presentation focuses on the team’s overall findings, analysis of the business problem, practical recommendations, proposed implementation approach and final conclusion. assessment Overview 1 Strong presentations are expected to be engaging, professionally structured and supported by relevant evidence, graphics, tables and other appropriate visual material. Higher-level work should move beyond description by applying theory critically to a real-world business problem, recognising the limitations and contextual applicability of theoretical concepts and producing recommendations that are appropriate to the organisation being analysed. assessment Overview 1 Overall, the assessment develops and evaluates project reflection, professional communication, teamwork, career planning, critical analysis, employability, problem solving and evidence-based business recommendation skills. It combines an individual reflective portfolio with a collaborative management-style presentation, allowing students to demonstrate both personal development and the ability to communicate project findings professionally.

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Software Engineering / Software Measurement and Process Models 2,000 words

Software Measurement, Goal–Question–Metric Analysis and Process Model Evaluation for DETO

This Measures and Models in Software Engineering coursework uses the Doolan Executive Taxi Service Online (DETO) case study to assess the application of software measurement techniques, Goal–Question–Metric analysis and software process modelling. The assignment requires students to connect quantitative software-engineering measures with practical organisational objectives and to critically evaluate suitable development-process approaches for a safety- and reliability-sensitive software system. 7COM1024_MMSE_ Def_CW_Brief 202… Task 1 focuses on software measurement using Unadjusted Function Points. Students analyse part of the DETO web-based email attachment system and identify relevant functional elements, including user inputs, reports to users, prompts and responses, interfaces to external systems or files, and internal logical files. Appropriate weights must then be selected to calculate the unadjusted functional-point value. 7COM1024_MMSE_ Def_CW_Brief 202… Task 2 requires application of the Goal–Question–Metric (GQM) approach to evaluate the effectiveness of the DETO website. Students identify the object under measurement and define the purpose, quality focus, viewpoint and context. They then develop two measurable organisational goals, formulate relevant questions for each goal and identify metrics that could be collected to evaluate website performance and support the company's priority of attracting new customers. 7COM1024_MMSE_ Def_CW_Brief 202… Task 3 moves from software measurement to software process models. DETO is considering a sophisticated on-board navigation system for its next generation of vehicles, where fast development, high quality, reliability and integration with the existing website are strategically important. Students select two software process models and critically evaluate their suitability for the project. The discussion should compare their distinguishing characteristics against alternative approaches, identify development challenges, evaluate project risks and pitfalls, and propose appropriate risk-mitigation strategies. 7COM1024_MMSE_ Def_CW_Brief 202… The main discussion for Task 3 is limited to 2,000 words ±10% and must use the Harvard referencing system, with at least 10 sources expected. The brief specifically requires original prose and prohibits bullet points, lecture materials and diagrams for this section. 7COM1024_MMSE_ Def_CW_Brief 202… Overall, the assessment integrates functional software measurement, GQM-based metrics, process-model evaluation, software quality, reliability, systems integration and project risk management within a realistic software-engineering business scenario.

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Big Data Analytics / Machine Learning 3,000 words

Machine Learning on Big Data Using PySpark: Large-Scale Data Analysis and Predictive Modelling

This group-based Machine Learning on Big Data project requires students to apply machine learning techniques to a large real-world dataset using PySpark DataFrames and Spark machine-learning libraries. Students select a substantial dataset, ideally between approximately 300 MB and 1 GB, from sources such as Kaggle, workplace data or other valid repositories, and develop an end-to-end big-data analytics workflow. CN7030 CRWK 26T1 The project begins with data loading and preprocessing using PySpark. Students are expected to handle missing values, perform data normalisation and feature engineering, identify class imbalance and propose appropriate mitigation strategies. Where text datasets are selected, additional preprocessing may include stemming, lemmatization and TF-IDF representation. CN7030 CRWK 26T1 The modelling stage requires implementation of an appropriate machine-learning approach using PySpark MLlib or Spark ML. The brief expects a multiclass rather than binary classification problem and allows techniques including multiclass classification, ensemble learning, clustering and text mining. Students must justify their model choice and consider model robustness, bias and variance when attempting to improve predictive performance. CN7030 CRWK 26T1 Students then perform hyperparameter tuning using techniques such as grid search or random search and evaluate the resulting model with appropriate measures. Relevant evaluation outputs may include accuracy, F1-score, precision, recall and a confusion matrix. Results should also be visualised or clearly presented and interpreted to identify meaningful patterns and performance characteristics. CN7030 CRWK 26T1 The project additionally requires consideration of Legal, Social, Ethical and Professional (LSEP) issues. Students discuss potential ethical concerns associated with their dataset, including bias and privacy risks, and propose suitable mitigation strategies. The final work is consolidated into a single user-friendly HTML analytics report that clearly presents the group's preprocessing, modelling, optimisation, evaluation and interpretation. CN7030 CRWK 26T1 CN7030 CRWK 26T1 Overview word count: approximately 335 words. If you are also uploading the presentation separately to the Reference Library, that should be a second entry under “Presentations and Academic Posters”, because the presentation forms a distinct 40% component and assesses understanding of Spark, preprocessing, modelling, optimisation, evaluation and responses to examiner questions. CN7030 CRWK 26T1

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Cyber Security / Ethical Hacking / Penetration Testing 4,000 words

Ethical Hacking and Penetration Testing: Vulnerability Exploitation, Privilege Escalation and Mitigation

This Ethical Hacking and Penetration Testing coursework requires students to conduct a practical CTF-style penetration test against a set of authorised target machines and produce a professional technical report documenting the compromise of one selected target. The assessment evaluates practical exploitation skills alongside the ability to analyse risk, explain attack vectors and recommend effective security controls. 8598ba8d8fff5a38af8d427a4ce8f84… The practical element requires students to identify vulnerabilities in multiple target systems, exploit those weaknesses to gain low-privileged access and then perform privilege escalation to obtain root-level access. Successful completion of each stage produces flags, with separate user and root flags contributing directly to the practical marks. Brief descriptions of the attack vectors and payloads used must also be recorded. 8598ba8d8fff5a38af8d427a4ce8f84… The written report focuses in detail on one compromised machine. Students must explain the reconnaissance and vulnerability-identification process, including the techniques used to discover services, web content and potential attack surfaces. The marking criteria specifically recognise appropriate reconnaissance tools such as Nmap and FFUF and reward clear justification of methods and links between reconnaissance results and identified threats. 8598ba8d8fff5a38af8d427a4ce8f84… 8598ba8d8fff5a38af8d427a4ce8f84… A further component requires a formal risk rating for the discovered vulnerabilities. Students should use a recognised risk-classification approach, such as OWASP or SANS, justify the assigned severity and discuss relevant social, legal and ethical considerations. Higher-performing work is expected to connect those considerations directly to the specific vulnerabilities identified. 8598ba8d8fff5a38af8d427a4ce8f84… The exploit section should explain the technical cause of the vulnerability, describe the exploitation process and present relevant example payloads. Mitigation recommendations must then be linked directly to the vulnerabilities discovered, with clear explanations of where the weakness occurs and how it can be remediated. 8598ba8d8fff5a38af8d427a4ce8f84… Overall, the coursework integrates reconnaissance, vulnerability analysis, exploitation, privilege escalation, risk assessment, ethical and legal considerations, technical reporting and defensive mitigation within an authorised penetration-testing environment. Important: this brief states that it is for Coventry University Group students' own use and must not be passed to third parties or posted publicly. 8598ba8d8fff5a38af8d427a4ce8f84… So for your public Reference Library, use an original summary like the one above rather than uploading the assessment brief itself.

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Operations Management / Business Simulation / Process Improvement 3,500 words

Operations and Simulation Analysis: Sam’s Sandwich Shop

This operations-management portfolio uses the Sam’s Sandwich Shop case study to examine service-process performance, simulation modelling, resource planning and operational improvement within a busy takeaway food environment. The case concerns a small sandwich outlet located in the departure lounge of Heathrow Airport Terminal 5, where rising terminal capacity is expected to increase customer demand over a five-month period. Students investigate how the store’s current sandwich assembly and service process performs under this growing demand and identify opportunities for operational improvement. MGT4924 Assignment instructions… The assessment consists of three related tasks. Task 1 – Arena Simulation Model requires students to develop a valid and functioning discrete-event simulation of the current system using Arena Simulation software. The model must accurately represent customer arrivals, ordering and payment, movement between the service counter and sandwich assembly area, preparation of meat, cheese and vegetarian sandwiches, resource constraints, queues and the possibility of sandwiches being rejected and remade. A commentary of up to 500 words must be included within the model to explain its main components and operation. MGT4924 Assignment instructions… MGT4924 Assignment instructions… The case provides defined operational resources, including three servers, two cash registers, one meat counter, one cheese counter and one vegetarian counter. The same server completes the full customer-service cycle, and customers join a single FIFO queue when both a server and cash register are not immediately available. The simulation must run for one week, equivalent to 168 hours, using multiple replications. MGT4924 Assignment instructions… Task 2 – Simulation Report requires a professional 1,000-word report analysing the system’s performance across the five-month period using results generated from the simulation study. Students must conduct experiments to determine suitable resource levels for each month and provide justified recommendations concerning the number of resources required for optimal operational performance. Tables and figures must be created independently in Excel rather than copied directly from Arena outputs. MGT4924 Assignment instructions… Task 3 – Operations Report requires a 2,000-word critical report examining two operations-management concepts in the context of Sam’s Sandwich Shop and the wider takeaway-food sector. Students analyse how the selected concepts are or could be implemented, identify associated operational problems and impacts, evaluate potential solutions, and consider relevant tools, techniques, methods and emerging technologies that could improve performance and competitive advantage. Two detailed and justified recommendations must be provided for each selected concept. MGT4924 Assignment instructions… Overall, the portfolio integrates discrete-event simulation, process analysis, resource optimisation, operational performance measurement and evidence-based operations-management decision making. Strong submissions are expected to move beyond simply reporting simulation outputs by critically analysing performance, evaluating experimental results, presenting high-quality data visualisations and producing logical, well-justified operational recommendations. MGT4924 Assignment instructions…

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Software Engineering / Enterprise Systems Development 3,000 words

Enterprise Software Engineering Development: ParkaLot Parking Management System Analysis, Design and Prototype

This Enterprise Software Engineering Development assessment is based on the ParkaLot Group, a fictional operator of multi-storey parking garages across major UK cities. The organisation currently relies on fragmented manual processes, basic barrier-based vehicle counting, local spreadsheets, on-site payment and inconsistent customer access arrangements. Students act as software engineering consultants and are required to analyse these operational weaknesses and design a centralised enterprise parking management system capable of supporting reservations, customer accounts, vehicle identification, billing, real-time occupancy monitoring, dynamic pricing and management reporting. COMP1471 CW 2526 The proposed ParkaLot platform is intended to integrate customers, parking spaces, reservations and billing across the garage network. Planned functionality includes online registration and reservation, recurring and corporate parking arrangements, licence-plate recognition, automated space allocation, sensor-based occupancy tracking, centralised monthly billing, electronic payments, promotional pricing and predictive overbooking. The system must also provide dashboards and historical reporting to assist management with capacity planning, staffing, pricing and operational decision-making. COMP1471 CW 2526 The coursework is completed in two main development phases. Phase 1 – Structured Analysis and Design requires an Entity Relationship Diagram representing the logical data model, a Data Flow Diagram including a Level 0 context diagram, and implementation of a prototype database. Phase 2 – Object-Oriented Development extends the system using object-oriented analysis, design principles and UML, with substantial business and user-interface functionality implemented using suitable OO technologies. COMP1471 CW 2526 The final report contains analysis of the 5 Ps of software engineering: Problem, Process, Project, Product and People. Students discuss the business problem and commercial risks, justify the development methodology followed, define resources and budget, document project artefacts and requirements, and identify the main stakeholders involved in the project. The technical design section includes the ERD, DFD, UML use-case model, at least three sequence diagrams, a detailed class diagram and discussion of design patterns. COMP1471 CW 2526 Students must additionally submit a functioning prototype that reflects the design and participate in acceptance testing and a live demonstration. Individual students are questioned on both theoretical and technical aspects of the submitted system. The assessment also evaluates group contribution, peer and self-assessment, personal reflection, research quality, communication and professional teamwork. COMP1471 CW 2526 The weighting places substantial emphasis on technical design and implementation: the UML design is worth 24 marks, the software prototype 15 marks, design patterns 6 marks, and acceptance testing/demonstration 25 marks. This makes the coursework strongly focused on demonstrating the relationship between requirements analysis, software architecture, UML modelling, implementation quality and working enterprise-system functionality. COMP1471 CW 2526

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Data Science / Data Management / Leadership and Entrepreneurship 4,500 words

The Data Science Professional: Tesla Data Management, Leadership and Entrepreneurial Practice

This interdisciplinary Data Science Professional assessment uses Tesla as the central organisational case study to examine how data management, leadership, entrepreneurship, technology and ethics interact within a contemporary technology-driven business. Students produce an individual report of 4,500 words equivalent, combining technical data-science competencies with strategic and managerial analysis. The Data Science Professional A… The Data Science Professional A… Part A – Database Design and Distributed Frameworks focuses on data management. Students design an Entity-Relationship model for Tesla-related organisational data, translate the model into a relational schema and justify the database structure. They also work with a specified database to produce Oracle SQL queries for analytical requirements. A further component critically evaluates the security, privacy and ethical implications of Tesla's Full Self-Driving technology, supported by relevant academic evidence. The Data Science Professional A… Part B – Leadership and Developing People requires critical analysis of Tesla's leadership model and organisational culture. Students examine current leadership challenges and their implications for organisational and employee performance before proposing a leadership and people-development strategy designed to support future organisational growth, employee engagement and sustained performance. The Data Science Professional A… Part C – Entrepreneurial Practice and Managing Risk investigates the proposed creation of a Tesla spin-out venture focused on innovative, low-cost green hydrogen production systems. Students critically evaluate management support for the entrepreneurial initiative and recommend an evidence-based course of action. They must also propose a multidimensional approach to mitigating entrepreneurial risks and barriers, critically assess entrepreneurial leadership characteristics, and develop a role descriptor for the person who would lead the new venture. The Data Science Professional A… The final element examines whether GDPR and data or AI ethics constrain or support entrepreneurial practice among employees. Overall, the coursework integrates database modelling, SQL, data governance, leadership development, organisational culture, entrepreneurship, innovation, risk management and ethical decision-making within a single applied case study. The Data Science Professional A… Important for the public Reference Library: the brief explicitly states that it is for Coventry University Group students' own use and must not be passed to third parties or posted on any website. The Data Science Professional A… So publish an original high-level overview like the one above, but do not upload the original assessment brief itself to the public library.

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Data Science / Data Analytics

Airline Passenger, Ticket Price and Revenue Analysis Using Python

This applied Data Science project requires students to use Python to analyse passenger demand, ticket prices and airline revenues across the period 2021–2023. Two datasets are provided: one containing daily passenger counts and revenue or average-price information for 2021 and 2022, and another containing a representative sample of individual journeys made during 2023. The datasets may include domestic, European and intercontinental routes as well as standard/economy and business/club travel classes. 202526_SmallProject_semB Students must develop Python code that reads the assigned datasets and produces a series of analytical visualisations. A core requirement is to plot daily passenger numbers for economy and business classes across all three years, combining scatter plots with smoothed trend lines. The smoothing must be calculated using the first eight terms of a Fourier series through the supplied scrfft.py module. 202526_SmallProject_semB Further analysis examines changes in average ticket prices, including monthly comparisons across 2021, 2022 and 2023, together with annual average prices that incorporate revenue generated from additional services such as seat reservations and extra baggage. 202526_SmallProject_semB A fourth analysis is personalised according to the final digit of the student's ID. Depending on the allocated task, students may investigate weekly journey distributions, seasonal travel patterns, price-versus-distance relationships, business and economy class behaviour, additional-service revenues, weekend journeys or linear relationships between selected variables. Three additional numerical values, labelled X, Y and Z, must also be calculated according to the assigned scenario. 202526_SmallProject_semB The final report must include four figures, relevant mathematical formulae and a critical discussion of the findings. Students are expected to interpret trends in passenger numbers, prices, revenues, seasonal patterns and airline profitability rather than simply presenting calculations. The report is limited to five A4 pages, while the Python source code and report are submitted separately. 202526_SmallProject_semB Overview word count: approximately 330 words. Note: the university name is not printed directly in the visible assignment heading, but the submission instructions use a herts.ac.uk module-leader address and StudyNet/Canvas, which identifies the institution as the University of Hertfordshire. 202526_SmallProject_semB

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Digital Forensics / Cyber Security 3,000 words

Digital Forensics Investigation of a USB Device: Evidence Acquisition, Analysis and Reporting

This Digital Forensics assessment requires students to undertake a simulated professional investigation of a USB storage device while acting as a digital forensic trainee for a fictional forensic-services organisation. The nature of the suspected wrongdoing is initially unknown, requiring the investigator to apply appropriate forensic methodologies, tools and analytical techniques to identify suspicious activity, recover relevant artefacts and determine whether evidence of malicious or unauthorised behaviour exists. 7070SCN_Assessment Brief_2526MA… The investigation begins with authorisation, evidence handling and chain of custody. Students must demonstrate secure receipt and management of the USB device, operate within the authorised scope of the investigation and maintain records covering each stage of the evidence lifecycle. Forensic acquisition requires use and validation of a software write blocker, creation of bit-for-bit forensic images and cryptographic hashing to demonstrate that working and evidential copies maintain integrity. 7070SCN_Assessment Brief_2526MA… The analytical stage involves examination of the working forensic image using appropriate digital-forensic tools. Students investigate file-signature mismatches, password-protected files, registry artefacts, USB history, user activity, metadata and timeline relationships. Where suspicious executable files are discovered, static and/or dynamic malware analysis may be undertaken. The investigation can therefore span documents, images, applications, executables and registry hives. 7070SCN_Assessment Brief_2526MA… Students must maintain objective and chronological forensic case notes documenting evidence acquisition, preservation, analysis and interpretation. These records should support reproducibility and potential evidential admissibility. The final forensic report summarises findings, explains and justifies the tools and methodologies used, records integrity-verification results, discusses relevant legal, ethical and professional principles and provides appropriate recommendations for further action. 7070SCN_Assessment Brief_2526MA… The assessment also encourages advanced forensic analysis where relevant, including OSINT, password recovery or decryption, data carving, regular-expression searching, advanced registry analysis and static or dynamic malware investigation. Professional practice is assessed through adherence to recognised forensic methodologies, industry best practice, legal and ethical obligations, chain-of-custody records and evidence-handling procedures. 7070SCN_Assessment Brief_2526MA… Overall, the coursework integrates forensic acquisition, evidence preservation, artefact analysis, advanced investigation techniques, professional documentation and legally defensible reporting within a realistic digital-forensics case-study environment. Important for your public Reference Library: this brief explicitly states that it is for Coventry University Group students' own use and must not be passed to third parties or posted on any website. 7070SCN_Assessment Brief_2526MA… So use the metadata and an original high-level overview like the one above, but do not upload or publicly reproduce the assessment brief itself.

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Data Mining / Data Science

Customer Service Escalation Risk Analytics Using Data Mining and Machine Learning

This advanced Data Mining assessment applies the Knowledge Discovery in Databases (KDD) process to a realistic customer-service risk scenario. Acting as a Data Scientist, students analyse a historical Customer Service Escalation Risk dataset to help an organisation identify early indicators of dissatisfaction and operational bottlenecks that may lead to serious or legal customer escalations. The resulting analysis is intended to support strategic decisions relating to staffing, employee training, customer-journey improvement and escalation prevention. CMP-7023B_Assessement_2 (2) The dataset incorporates customer demographics, account characteristics, communication channels, issue categories, operational measures such as waiting times, transfers and SLA breaches, behavioural indicators including sentiment and response delays, and commercial variables such as monthly fees and contract value. The target variable, escalation_level, contains four categories: No escalation, Minor escalation, Serious escalation and Legal escalation. CMP-7023B_Assessement_2 (2) Students begin with data exploration and visualisation, producing appropriate descriptive statistics and identifying patterns, distributions and potential data-quality concerns. They then perform data cleansing, transformation, feature engineering and preprocessing. Variables that may introduce leakage or unreliable predictions because of their meaning, timing or quality must be critically assessed and justified. CMP-7023B_Assessement_2 (2) The supervised-learning stage requires students to develop, tune and compare predictive models using techniques such as k-nearest neighbours, Decision Trees, Support Vector Machines, ensemble methods or neural networks. Appropriate multiclass evaluation metrics must be used, alongside interpretation of influential variables and model behaviour. CMP-7023B_Assessement_2 (2) The assessment also includes unsupervised learning, requiring comparison of clustering methods such as K-Means and hierarchical clustering after removal of the target variable. Students may apply encoding, normalisation and dimensionality-reduction methods such as PCA or t-SNE and must interpret how the resulting clusters relate to escalation behaviour. CMP-7023B_Assessement_2 (2) Overall, the project assesses independent analytical judgement, modelling justification, comparative evaluation and clear communication of actionable findings for both technical and executive audiences. CMP-7023B_Assessement_2 (2) Overview word count: approximately 340 words. AI-use note: AI tools may only assist with small, specific code snippets. Any AI-generated code must be clearly acknowledged and cited, while the analysis, coding decisions, interpretation and final evaluation must remain the student's own work. CMP-7023B_Assessement_2 (2)

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Cybersecurity / Security Operations

Catnip Games International: SOC Automation and Incident Response Platform

This cybersecurity project presents the design and implementation of a prototype Security Operations Centre (SOC) automation and incident-response platform for Catnip Games International. The scenario addresses security challenges affecting a gaming organisation operating more than 300 Linux servers across two data centres, including credential-stuffing bot attacks, compromised player accounts, phishing campaigns and delayed coordination during security incidents. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete The proposed solution integrates TheHive 5, Cortex 3, Elasticsearch, Cassandra and Python-based automation, with MISP explored for threat-intelligence integration. TheHive functions as the central incident and case-management platform, Cortex provides automated observable analysis, Elasticsearch supports search and log storage, Cassandra provides persistent case and alert storage, and Python scripts automate alert ingestion and workflow activities through REST APIs. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete Implementation includes environment configuration, Docker deployment, API integration, automated alert generation, incident-response playbooks, KPI monitoring and backup procedures. Three attack scenarios are modelled: bot attacks, account takeover and phishing. Alerts are automatically ingested into TheHive, converted into cases and processed through analyst triage, investigation and resolution workflows. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete The project also develops structured response playbooks covering triage, containment, investigation, recovery and post-incident actions for each security scenario. Operational metrics are visualised through a KPI dashboard measuring alert volumes, response times, Mean Time to Detect (MTTD), Mean Time to Respond/Resolve (MTTR) and platform availability. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete Overall, the work demonstrates practical application of SOC architecture, security automation, incident management, threat analysis, containerised infrastructure, API-based integration, operational metrics and cyber-response procedures within a realistic gaming-industry security scenario. Catnip_Games_SOC_Complete Overview word count: approximately 330 words. Important before putting the presentation on a public Reference Library: redact any API keys/authentication tokens and other live credentials shown in the technical slides. The presentation includes API-key material in the Cortex and Python automation sections, so those credentials should also be revoked/rotated if they were ever active. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete

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Computer Networks / Network Security / Cloud and Software Defined Networking 3,500 words

Network Systems and Security: Ad Hoc, Cloud and Software Defined Networking Emulation

This Network Systems and Security coursework requires students to design, implement and critically evaluate a series of practical network-emulation environments covering wireless Ad Hoc networking, cloud services and Software Defined Networking (SDN). The project combines Python-based network configuration with practical connectivity testing, cloud deployment, controller-based networking and theoretical evaluation of contemporary network-security technologies. The first task involves designing an Ad Hoc wireless network representing an emergency-response scenario. Students configure at least three wireless stations using Mininet-WiFi, assign appropriate network parameters and demonstrate connectivity through ICMP communication. The task requires discussion of the design and implementation together with the Python script used to configure the emulated environment. 7COM1076+ref+def+CW+2025+26+ The second task focuses on cloud-service emulation. Students develop a simple static website, deploy it through Render.com and GitHub, and access the hosted service from a Mininet-emulated network. Required evidence includes the Python implementation, cloud configuration screenshots, commands used to provide internet connectivity, webpage access through an xterm environment and the associated HTML code. 7COM1076+ref+def+CW+2025+26+ The third practical component examines Software Defined Networking using the ONOS controller. Students construct an emulated topology containing hosts, servers and programmable switches, demonstrate complete ICMP connectivity and perform a TCP transmission lasting 600 seconds. Evidence must include the network-emulation script, ONOS graphical interface and connectivity results. 7COM1076+ref+def+CW+2025+26+ The final analytical section critically evaluates whether Software Defined Networking and Network Functions Virtualisation (NFV) complement one another and examines security algorithms used within cloud computing. Students compare two selected cryptographic approaches, evaluating their respective advantages and disadvantages. 7COM1076+ref+def+CW+2025+26+ Overall, the coursework integrates network modelling, wireless networking, cloud deployment, SDN control, Python scripting, connectivity testing and security analysis. The marking scheme gives substantial weight to system modelling, cloud and SDN implementation, ICMP/TCP functionality, technical analysis and overall report quality. 7COM1076+ref+def+CW+2025+26+

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Business Consultancy / Digital Marketing / Social Media Marketing 3,000 words

You Keep Me Sane: Social Media Growth and Digital Product Marketing Live Business Project

his Extended Work Project is a live business consultancy assignment completed for You Keep Me Sane, a podcast and social-media brand seeking to expand its online audience and increase sales of its digital products. The organisation promotes its podcast across platforms including Instagram, Facebook, TikTok, YouTube and LinkedIn and identified a need for additional support with regular content creation, social-media scheduling and digital-product promotion. Project Brief_You Keep Me Sane … The client challenge focuses on improving the organisation's social-media presence while reducing the workload associated with producing and publishing content. The project brief specifically identifies the need to create reels, carousels and other social-media posts, potentially using Canva, and to support an existing Buffer-based scheduling process. The organisation aims to publish approximately three times per week while also promoting new digital products. The intended commercial outcomes are growth in social-media following and increased digital-product sales. Project Brief_You Keep Me Sane … The academic assessment requires students to document the project journey in chronological order, from the initial client brief and early meetings through planning, research, idea development, feedback, implementation, challenges and final outcomes. The 3,000-word report should explain the business context, methods and frameworks used, significant milestones, problems encountered, adaptations made and recommendations provided to the client. EWP 5TH MAY 2026 (1) EWP 5TH MAY 2026 (1) Professional reflection is also an important element of the project. Students are expected to evaluate team learning, skills development, project-management experience and the practical lessons gained from working on a genuine business challenge. The report should demonstrate critical thinking and reflective analysis rather than simply describing activities completed. EWP 5TH MAY 2026 (1) The accompanying 10-slide presentation mirrors the report and communicates the project overview, organisational background, initial brief, research, development process, challenges, outcomes, recommendations and learning in a concise visual format. EWP 5TH MAY 2026 (1) Overall, the project integrates live business consultancy, social-media strategy, content development, digital-product marketing, client engagement, teamwork, project management and reflective professional learning, with emphasis on demonstrating practical value created for the client organisation.

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Leadership / Digital Leadership / Business Management 4,000 words

Leadership in a Digital Age: Critical Self-Analysis, AI Transformation and Personal Development

This Leadership in a Digital Age assessment requires students to critically analyse their leadership strengths, behaviours and development needs within contemporary digital environments. The individual 4,000-word report combines academic leadership theory, diagnostic self-assessment, professional reflection, digital transformation and forward-looking personal development. Its central purpose is to demonstrate self-awareness and evaluate how leadership capabilities must evolve in response to technological, organisational and workforce change. NUL Assessment Brief LD7090 202… The first section requires critical evaluation of two or three contemporary leadership theories or models in relation to digital leadership. Students should avoid outdated approaches and instead examine how relevant theories align with the behaviours and characteristics required of leaders operating in technology-enabled organisations. NUL Assessment Brief LD7090 202… The second section focuses on self-analysis. Students use diagnostic tools relating to areas such as temperament, workplace culture, motivation, emotional control, management skills and Belbin team roles. Results should be reported and interpreted before being used to construct a personal SWOT analysis concentrating specifically on leadership characteristics relevant to the digital age. NUL Assessment Brief LD7090 202… A further component examines the leadership of hybrid, multi-generational teams. Students identify challenges that may arise in such environments and evaluate leadership capabilities and behaviours that could address them. Ethical, social and legal responsibilities associated with digital leadership must also be considered. NUL Assessment Brief LD7090 202… The report additionally evaluates how digital leaders can use Artificial Intelligence to support digital transformation and organisational performance. Appropriate workplace examples may involve machine learning, predictive analytics, intelligent automation or generative AI, with consideration of required resources such as data infrastructure, organisational skills and external partnerships. NUL Assessment Brief LD7090 202… The final section requires a Personal Development Plan containing justified leadership-development objectives, learning activities, measurable success criteria and timescales. These objectives should emerge directly from the earlier self-analysis and demonstrate how the student intends to become a more effective leader in a current or future digital role. NUL Assessment Brief LD7090 202… Overall, the assessment integrates leadership theory, reflective self-evaluation, hybrid-team management, AI-driven transformation and structured professional development within the context of leadership in the digital age.

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Machine Learning / Cloud Computing / Artificial Intelligence 4,004 words

Cloud-Based Machine Learning for Financial Fraud Detection

This Machine Learning on Cloud assessment requires students to design, implement and critically evaluate a cloud-oriented machine-learning solution for financial fraud detection. Working as a group, students address a scenario in which a financial-services organisation requires an automated model capable of detecting fraudulent transactions, reducing financial losses and improving customer security. The project combines machine-learning development with critical evaluation of cloud infrastructure, data preparation, model performance and responsible AI considerations. NUL - LD7187 -Assessment Brief … The project begins with a cloud feasibility study comparing at least two major machine-learning platforms such as Microsoft Azure, Amazon Web Services and Google Cloud Platform. Students evaluate factors including performance, scalability, cost, compliance, system integration and vendor lock-in before providing a justified recommendation. The project then moves into Exploratory Data Analysis, where patterns, anomalies and correlations within the fraud dataset are investigated using visualisations such as heatmaps, histograms and boxplots. NUL - LD7187 -Assessment Brief … A substantial part of the assessment focuses on data preprocessing and class imbalance. Students are expected to clean and transform the dataset, apply scaling and encoding, perform feature engineering and investigate techniques such as SMOTE, undersampling and cost-sensitive learning. These decisions must be justified in terms of their potential effect on predictive performance. NUL - LD7187 -Assessment Brief … Students must then select and train at least two machine-learning models. Suggested algorithms include Logistic Regression, Random Forest, XGBoost and Neural Networks. Appropriate cross-validation and hyperparameter-tuning procedures should be applied, followed by systematic evaluation using precision, recall, F1-score, AUC and precision-recall curves. Supporting visualisations should include confusion matrices, ROC curves and feature-importance analysis. NUL - LD7187 -Assessment Brief … The final component addresses professionalism and ethics in cloud-based AI, including bias, fairness, transparency, data privacy and environmental sustainability. Overall, the project integrates cloud-platform selection, exploratory analytics, preprocessing, imbalanced-data handling, predictive modelling, model evaluation and ethical AI into an applied financial fraud-detection solution. NUL - LD7187 -Assessment Brief … Note: the uploaded brief does not explicitly name a referencing system. If your portal requires a selection, I would use Not specified rather than assume Harvard.

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Machine Learning / Cloud Computing 2,000 words

Technical Evaluation and Professional Reflection on a Cloud-Based Machine Learning Fraud Detection Solution

This postgraduate individual assessment critically evaluates a cloud-based machine learning solution for financial fraud detection developed as part of a preceding group project. The scenario concerns a financial services organisation seeking to detect fraudulent transactions in order to reduce financial losses and strengthen customer security. The individual report requires students to examine both the technical quality of the developed solution and their own professional contribution to the project. NUL - LD7187 -Assessment Brief … The first component, Technical Evaluation, accounts for 50% of the assessment and has a suggested allocation of approximately 1,000 words. Students critically analyse the group solution with particular attention to data preprocessing, machine learning model choices, evaluation metrics and technical limitations. The analysis should go beyond description by explaining how specific modelling and design decisions influenced the final outcomes of the fraud-detection system. NUL - LD7187 -Assessment Brief … The second component, Reflection and Professional Issues, also accounts for 50% and is approximately 1,000 words. Students critically reflect on their personal contribution, teamwork experience, challenges encountered and lessons learned during the project. The discussion also addresses wider professional and ethical considerations associated with AI and cloud-based machine learning, including bias, fairness, sustainability and data privacy. NUL - LD7187 -Assessment Brief … The assessment is designed to demonstrate critical understanding of machine learning methods, cloud-computing architectures, practical development of machine learning solutions and awareness of the social, ethical and sustainability implications of AI technologies. A Seminar Activity Tracker must also be included as an appendix to provide evidence of weekly participation and knowledge development. NUL - LD7187 -Assessment Brief … NUL - LD7187 -Assessment Brief … Higher-level performance requires a comprehensive connection between technical decisions and outcomes alongside deep reflection on teamwork, professional development, ethics, fairness and sustainability. NUL - LD7187 -Assessment Brief … Overview word count: approximately 300 words. AI-use note: the brief permits AI for limited support such as grammar improvement, structure, organising ideas and suggestions. The student's main content, analysis and conclusions must remain their own, and any AI use must be declared. NUL - LD7187 -Assessment Brief …

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Statistical Programming / Data Science / Business Analytics

Statistical Programming with R: Data Analysis, Probability, Regression and Business Decision-Making

This Statistical Programming assessment evaluates students' ability to apply statistical techniques and R programming to practical data-science and business decision-making problems. The individual assessment combines descriptive statistics, data preparation, visualisation, probability, regression, correlation and sampling, requiring students to demonstrate both conceptual statistical understanding and practical implementation in RStudio. The module learning outcomes emphasise the application of statistical methods to large and real-world datasets, critical evaluation of analytical techniques and awareness of legal, cultural and ethical issues associated with data analysis and dissemination. KL7012 - Statistical Programmin… The early tasks examine fundamental statistical reasoning. Students interpret weight-loss data comparing exercise classes with gym-only workouts using sample size, mean, mode and standard deviation, and explain an appropriate method for dealing with missing data, including its advantages and disadvantages. KL7012 - Statistical Programmin… A substantial practical component uses a cystic fibrosis dataset containing variables such as age, sex, height, weight, body-mass-related measurements, forced expiratory volume, residual volume, functional residual capacity, total lung capacity and maximum expiratory pressure. Students import the data into an R data frame, generate descriptive summaries and interpret the results. They then use scatterplots to investigate relationships between variables and sex-stratified boxplots to identify possible outliers. KL7012 - Statistical Programmin… The assessment also covers major probability models. Students apply probability concepts to healthcare survival, helpdesk email arrivals and fuel-demand scenarios, while also discussing how changing assumptions or real-world conditions can affect interpretation. These exercises assess understanding of statistical distributions and their application to operational and managerial decision-making. KL7012 - Statistical Programmin… Further analytical tasks examine linear regression and correlation. Students analyse the relationship between temperature and converted sugar in a chemical process, use a regression model to estimate the expected response at a specified temperature, and interpret relevant summary statistics. They also calculate and evaluate the suitability of a correlation coefficient for examining the relationship between advertising activity and product purchases. KL7012 - Statistical Programmin… The final and most substantial task involves a real-world M1 traffic-speed investigation for a manufacturing organisation. Students must design an appropriate sampling strategy, collect data from the specified Traffic England source, conduct statistical analysis in RStudio and develop evidence-based conclusions. The statistical report for this task is limited to 1,500 words and should include sampling methodology, collected data, statistical analysis, results, conclusions and relevant background research, supported by appropriate graphs, tables and charts. Raw data and RStudio calculations must be included in an appendix. KL7012 - Statistical Programmin… Overall, the assessment integrates statistical theory with R-based practical analysis, covering descriptive statistics, probability, visualisation, missing-data treatment, regression, correlation, sampling and critical interpretation of results in healthcare, operational and business contexts.

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Information Visualisation / Data Analytics / Data Science 1,500 words

Information Visualisation Project Using Power BI and Python

Assignment overview — ready to paste This Information Visualisation project requires students to design, implement and critically evaluate effective data visualisations using two different technological approaches: Microsoft Power BI and Python. The assessment focuses on the practical application of information-visualisation principles, including data preparation, visual design, interaction, audience requirements and the extraction of meaningful patterns and insights from complex datasets. Assignment 002 Coursework 2025-… Task 1 focuses on interactive visualisation using Power BI. Students work with the UK Department for Transport's Road Safety Open Data (STATS19), which contains information relating to road traffic accidents, casualties, vehicles, locations, times and contributing factors. Students may analyse one year or multiple years of data depending on their visualisation objectives. Assignment 002 Coursework 2025-… The Power BI work requires students to identify an appropriate target audience and report type, select relevant variables, clean and transform the data, develop an appropriate data model and create analytical measures using Data Analysis Expressions (DAX). The resulting dashboard should communicate the context of the data and reveal meaningful trends, patterns and insights. Assignment 002 Coursework 2025-… Task 2 requires students to develop visualisations programmatically using Python, with Jupyter Notebook recommended as the implementation environment. Students independently select a real-world, publicly available dataset containing at least 10,000 observations and more than five variables. Unlike Task 1, visualisation tools that automatically construct visualisations, such as Tableau or Power BI, cannot be used for this component because programming is an explicit requirement. Assignment 002 Coursework 2025-… Assignment 002 Coursework 2025-… The submitted Jupyter Notebook should operate as an educational technical report explaining the selected dataset, preprocessing procedures, visualisation choices and resulting insights. Students are expected to justify their visualisation techniques, critically evaluate findings and discuss challenges encountered during development. The textual content of the notebook is limited to 1,500 words, excluding code and visualisations. Assignment 002 Coursework 2025-… The complete assessment contains several deliverables, including a maximum 6-minute Power BI demonstration video, a maximum 2-page Power BI report, the .pbix file, an 8-minute Python/Jupyter visualisation demonstration, the Jupyter Notebook, dataset and README file. All materials must ultimately be packaged into a single ZIP submission. Assignment 002 Coursework 2025-… Assignment 002 Coursework 2025-… Important: the brief does not specify a named referencing style or academic level, so I would select Not specified for those two portal fields rather than guessing. It also explicitly states that generative AI must not be used to create any part of the assessed submission, including code, debugging, writing, paraphrasing or bibliographies. Assignment 002 Coursework 2025-…

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Global Business Strategy 2,500 words

Global Business Strategy – Strategic Analysis of a Global Company

This assessment is an individual portfolio for the Global Business Strategy module. The assignment requires students to conduct a comprehensive strategic analysis of a named global company that is facing a significant business problem and to develop strategic options that can support the organisation's sustainable growth and future success. The selected company can be from any industry and may be a large or small global organisation. Students must identify a company that has experienced significant challenges during the past five years or is currently facing strategic difficulties. These may include loss of market position, inability to gain or regain market share, operational challenges, or declining revenues and profits. The assessment requires students to investigate the company's strategic purpose, vision, mission and objectives before examining the internal and external global business environment that may have contributed to its challenges. Relevant strategic theories and models should be applied to support the analysis. The portfolio is developed progressively across the semester. The first stage focuses on selecting the global company, identifying its key problem and analysing the internal and external business environment. The second stage examines sustainable business strategies, diversification and competitive advantage through a resource audit, together with an appropriate model for supporting global business growth. Students must also propose an appropriate mode and strategy for entering an international market in which the selected company does not currently operate. The third stage focuses on strategic change, leadership and governance. Students are expected to demonstrate an understanding of effective leadership styles, the role of leadership in strategic change, good governance and the importance of ethics in international business. Practical examples should be used to demonstrate how leadership, governance and ethical considerations can contribute to business growth. The fourth stage addresses good strategy execution and evaluation. Students must justify how the proposed strategy can be effectively implemented using available organisational resources and process management tools that support continuous improvement. The analysis should lead to strategic recommendations and an evaluation of how the proposed strategies could affect the company's future performance and competitiveness in the global market. After completing the individual portfolio tasks, students must prepare a summary report of approximately 1,000–1,500 words. This report should synthesise the key learning and insights gained from each task and demonstrate how the different strategic concepts have been applied to the selected organisation. The final e-portfolio is compiled as a single academic report in PebblePad and submitted as a PDF through Turnitin. The overall report should be approximately 2,500 words ±10%, excluding references and appendices, and sources should be cited using the ULBS Harvard referencing style.

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Business Ethics 2,500 words

Success Through Business Ethics – Ethical Analysis of an FMCG Brand

This assessment is an individual written report for the Success Through Business Ethics module. The assignment requires students to critically examine ethical issues and challenges within a Fast Moving Consumer Goods (FMCG) brand and evaluate how ethical theories, decision-making approaches and leadership practices can be applied to understand unethical business behaviour. The report has a total word limit of 2,500 words and accounts for 100% of the assessment. Students are required to select an FMCG brand that has been involved in unethical practices between 2000 and 2025. The selected brand may originate or operate anywhere in the world and may still be operating or may have ceased operations. Students must ensure that sufficient information is available about the organisation and its external environment before selecting the company. The report begins with an introduction explaining the nature of business ethics and introducing the selected FMCG brand and the unethical business practices associated with it. The main analysis requires students to select three normative ethical theories, explain their key principles and critically evaluate whether the company's behaviour adhered to or violated those principles. Students must use this analysis to explain why the identified business practices can be considered unethical. A second analytical section requires students to choose either ethical decision-making or social accounting. The selected concept must be explained and then critically applied to the unethical practices of the chosen FMCG brand. A further analysis focuses on the leadership style of the company's leadership team. Students must explain the principles of the leadership style, consider its positive and negative aspects, and analyse how the leaders responded to the unethical business practices. The report concludes by summarising the key findings from the analysis and providing two important recommendations for the selected brand. The recommendations should be directly relevant to the unethical practices identified and should be justified using evidence and findings from the report. Where a selected company has ceased operating, recommendations should still be provided on the assumption that the brand is operating. The assessment develops students' ability to apply ethical frameworks to business decision-making, understand ethical decision-making and corporate social responsibility, align ethics and values with business contexts, analyse ethical challenges in business strategies and operations, and evaluate moral dilemmas using economic, legal and ethical considerations. The report must use Harvard referencing for in-text citations and the reference list, with the reference list organised alphabetically.

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Leadership and Professional Development 2,500 words

Leadership Mindset – Professional Development Portfolio

This assessment is a Leadership Mindset Professional Development Portfolio designed to encourage students to think strategically about their career development, align their professional goals and demonstrate leadership potential. The assessment focuses on self-awareness, strategic planning, professional behavioural skills and the ability to develop an ongoing process of personal and professional growth. Students are required to complete a Portfolio through PebblePad, equivalent to 2,500 words. The portfolio is assessed on a Pass/Fail basis and students must complete all required sections before downloading the completed portfolio and submitting it through Turnitin. The portfolio does not require academic referencing because it is a self-reflection and professional development assessment. The portfolio consists of several key components, including a personal SWOT analysis, evidence of communication requesting feedback, a Personal Development Plan (PDP), a CV and a cover letter. The SWOT analysis requires students to identify their strengths, weaknesses, opportunities and threats in order to understand their current skills, identify development gaps and recognise opportunities for improvement. Students must also reflect on the Professional Development Pyramid or another suitable professional development model and select three behavioural skills or competencies they wish to develop. Examples include strategic thinking and leadership. Feedback must be requested from four to six people from the student's personal and professional network, such as family members, friends, peers, mentors, employers or colleagues. This feedback is then used to support the student's development priorities. The action-planning section requires students to reflect on the feedback received and identify three development priorities or goals. For each priority, at least two SMART actions must be established. The action plan should include specific steps, timelines and required resources, while also identifying potential obstacles and explaining how these obstacles may be addressed. The goals and actions should demonstrate a clear connection between the student's self-reflection, feedback and professional development objectives. The final reflection considers the value of the PebblePad portfolio process in shaping personal and professional growth. Students are expected to demonstrate an in-depth understanding of self-development and explain how their development process can be reviewed, revised and adapted for continuing professional growth. The assessment learning outcomes focus on reflection on personal strengths and areas for improvement, advanced critical thinking, problem-solving and decision-making, intercultural communication, inclusivity and sustainability, interview and presentation competencies, and the ability to articulate an adaptable self-development process. The marking criteria emphasise self-reflection, clarity of goals, strategic action planning, persuasive understanding of professional development, and clear and professional presentation.

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Applied Data Science 500 words

Critique of a Data Science Book and Selected Chapter

This assignment requires students to critically evaluate a selected data science book and a specific chapter from that book. Students must choose one book from the list provided in the assignment, read the preface or introduction to understand the intended audience, and then select a chapter that is relevant to their interests, existing knowledge and learning objectives. The available books cover a range of data science and analytical subjects, including practical time series analysis, machine learning with Python, Python-based data science, technical analysis, Bayesian statistics and artificial intelligence applications. The main purpose of the assignment is to develop the student's ability to engage critically with technical literature rather than simply summarising its content. The critique should identify the selected book and its intended audience, clearly state the chosen chapter and explain the reasons for selecting it. Students are expected to consider what they hoped to learn from the selected material and then critically assess whether the chapter achieved these objectives. The assessment should consider the clarity, usefulness and accessibility of the material, as well as the extent to which it contributes to the student's understanding of data science concepts. Students should also discuss additional knowledge they would like to gain from the book and identify particular aspects that were either helpful or less useful. This may include the quality of explanations, examples, technical depth, practical applications, organisation of material and relevance to the student's existing knowledge. The critique should demonstrate engagement with the selected chapter and provide reasoned observations rather than simply describing what the author has written. The final submission is a 500-word critique with a permitted variation of plus or minus 10 percent, meaning the expected range is approximately 450–550 words. The text must be written as a continuous narrative and should not use subheadings for the individual assessment points. The headline should follow the format “Critique of <book title> by <book author>”, with the student's name and student ID as the subtitle. The assignment assesses both technical presentation and content, including grammar, writing style, word count, completeness, breadth and depth of the book assessment, critical analysis and evidence of engagement with the selected material. Students must submit text that can be processed by Turnitin.

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Computing

Independent Critical Analysis 30

Independent Critical Analysis 30 is an individual assessment that develops students' ability to critically analyse ethical, social, legal and professional issues arising from a computing-related scenario. The assessment is worth 30% of the overall module assessment and requires students to respond to three questions relating to the ethical and professional issues presented in the scenario. Students are expected to apply the specific analytical techniques or approaches identified in the assessment instructions when developing their responses. The assessment focuses on the critical examination of ethical issues and professional responsibilities within contemporary computing contexts. Students are expected to identify relevant ethical concerns and provide a reasoned justification for their analysis. The marking criteria emphasise the identification of a single ethical issue or ethical risk, followed by a structured analysis using the EHAZOP Framework. Higher-level responses are expected to provide clear justification for the ethical issue selected, examine the associated consequences, and demonstrate a systematic and critical approach to the scenario. A second component focuses on ethical risk analysis using the Ethical OS Toolkit. Students are expected to identify an ethical risk associated with the scenario and justify their selection through a structured analysis. The assessment therefore requires students to consider the potential consequences of computing-related decisions and to demonstrate an understanding of how ethical risks can be identified and evaluated. The final component addresses professional issues. Students are expected to identify relevant professional principles and apply an appropriate professional code of conduct, such as the ACM or BCS Code of Conduct, to the scenario. The analysis should explain which professional principles are relevant and provide a reasoned justification for their application. The marking criteria place emphasis on systematic analysis, appropriate justification and understanding of responsible computing practice. The assessment therefore connects ethical decision-making with professional responsibilities and standards. The assignment also assesses broader module learning outcomes relating to ethical standards, contemporary computing contexts, legal and professional issues, and the ability to critically analyse high-profile cases or case studies. Students are required to submit the provided answer sheet containing the scenario and three questions. The assessment brief states that submissions are subject to Turnitin and that students must follow the specified submission requirements.

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Operating Systems and Networks 2,000 words

Security of Operating Systems and Networks – Individual Assignment

This individual assignment focuses on the security of operating systems and computer networks. Students are required to produce a professional technical report of approximately 2,000 words demonstrating a deep and systematic understanding of operating-system security, networking functions, security threats, vulnerabilities and practical security testing. The assessment carries 50% and forms 100% of the module assessment. Students are expected to support their work with appropriate technical evidence, images showing practical steps and relevant sources. The assignment uses a business scenario involving Net-Tech, a small and medium-sized technology-services enterprise. The organisation is concerned about the security of its proposed system, including operating-system attacks such as buffer overflow and network threats such as hacking and phishing. Students are required to investigate, design and experiment with the features and functions of a web server used to serve the company's website, while assessing the security landscape and presenting findings that can support appropriate organisational security decisions. As part of the practical work, students must create a prototype Net-Tech network test rig. This includes creating two users, with one configured as a superuser and another as a standard user, applying appropriate baseline security measures, installing suitable software and identifying vulnerabilities, using appropriate tools to conduct security tests, and writing scripts to automate repetitive tasks. Students must document assumptions and parameters used within the project, including further security implementations and recommendations such as the use of a suitable database for a database-driven website. The report is structured around introduction, background research, pre-engagement, engagement and post-engagement activities. The introduction should explain the business scenario, assumptions, aims, objectives, deliverables, available skills and resources, constraints and project plan. The background research should address common vulnerabilities, threats, risk models, security-testing approaches, relevant attack and testing tools, legal and organisational requirements, and ethical, social, professional and sustainability considerations. The pre-engagement section covers the test-rig setup and testing strategy. The engagement section requires practical comparison and demonstration of operating-system and network security, including user authentication, file and directory permissions, protection against stack-overflow attacks, network weaknesses, operating-system discovery, firewalls, listening ports, network statistics, prevention of denial-of-service attacks and scripting for automation. The post-engagement section requires a summary of the work, deductions and limitations, mitigation measures and recommendations, and personal reflection. The assessment requires students to use relevant sources, provide a bibliography and demonstrate appropriate analysis, evaluation and reflection. The assignment is designed to assess learning outcomes relating to knowledge of network security threats and the development of complex software and scripts relevant to operating systems and computer networks.

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Available Model Answers (100)

Managing the Global Supply Chain and Sustainability – Individual Company Case Analysis

Machine Learning on Big Data using PySpark

Business Consultancy Project – Summative Coursework

Global Engineering: Theory and Practice – Aspen Pharmacare Global Expansion and Environmental Sustainability

Problem Solving and Research Methods for Managers – Summative Assignment

Strategic Management in Healthcare – Strategic Analysis and Strategy Formulation

Generative Adversarial Networks – Building and Applying GANs to Real-World Problems

German Electricity Load Forecasting Using Time Series and Machine Learning Models

Literature Review – International Business Research

Assignment 3 – Large Language Models: LLM Coding and Report

Global Strategic Management – Linear to Circular Business Model Transformation

Financial Performance Management – Financial Performance, Balanced Scorecard and Integrated Reporting

Business Research Methods – Research Methodologies, Research Instrument and Research Dissemination

Fundamentals of Digital Technologies – Group Project and Individual Refinement

Individual Project – Image Segmentation

Internationalisation and Global Expansion Plan for a Small or Medium-Sized Enterprise

Develop a Change Management Plan for a Specific Organisational Context

Individual Reflective Report – Group Consultancy Project

Group Consultancy Report – Engineering and Environment Advanced Practice

Cloud and Big Data Technologies – Summative Assessment: Cloud and Big Data Security Application

Assessment #1 – Advanced Databases: NORTHERNTOURS Database Design and Implementation

Individual Reflection on Group Research Presentation

HopeLink Community Support and Food Security Database

Managing Customer Experience – Customer Experience Strategy Report

Leading Through Digital Change – Digital Transformation Report

Individual Reflection on Group Research Presentation and Research Skills Development

Operations and Supply Chain Management – Individual Reflective Report

Advanced Practice Research Project – Reflective Individual Report and Poster Presentation

Global Business Strategy: Strategic Analysis and Growth of a Global Company

Leadership in a Digital Age: Leadership Strengths and Development Needs

Financial Mathematics: Portfolio Analysis, Risk and Volatility Modelling

L7 Business Simulation – Cyber Security: Ethical Hacking and Vulnerability Assessment

Business Consultancy Project: Strategic Analysis of a Business Challenge

Applied Modelling and Visualisation – Hexawing Airways Passenger Satisfaction Analysis

Big Data and Cloud Computing: FieldVision Cloud-Based Big Data Solution for AgroNova

Critical Analysis of Management Practices at Apple Inc.

Digital Transformation Report and Poster

Customer Experience Strategy: Critical Evaluation of a Global Mobile Phone Brand

Personal Development Plan: Academic, Employability and Career Development

Suez Canal Blockage: A Case Study of Global Supply Chain Disruption

A Comparative Analysis of Cultural Factors Shaping Human Resource Staffing Strategies in International Enterprises

CW1: Applying advanced AI methods for analysing text documents

Individual Reflection on Case Study Discussion – International Business Strategy

Time Series Modelling Case Study – Oil Price Forecasting

Global Supply Chain Management – Gatwick Airport Northern Runway Expansion

Computational Algorithm Analysis – Research Paper Algorithm

Organisational Strategy and Sustainability: Strategic and Sustainability Analysis of Engineers & Planners Company Ltd

Critical Literature Review in Research Methods and Project Management

Physical Security Audit of University Computing Facilities Using ISO/IEC 27002:2022

Enterprise Business Start-up: Sustainable Business Plan, Fundraising Strategy and Entrepreneurial Reflection

Parallel Algorithms for Hierarchical Clustering: Single-Link, Minimum Spanning Trees and Parallel Architectures

Calculus and Optimisation: Python Implementation of Gradient Descent, Derivatives and Polynomial Regression

Entrepreneurial Marketing Business Idea Pitch: Market Opportunity, Value Proposition and Venture Viability

Critical Analysis of Computational Algorithms: Research Paper Evaluation and Complexity Analysis

Applying Advanced AI Methods for Analysing Text Documents

MindBand: A Creative Marketing Plan for a Mental Wellbeing Wearable in the UK Smart Device Market

Individual Reflection on Tencent’s Strategic Reorganisation and International Business Strategy

Data-Driven Marketing Analytics: Google Analytics 4 and Google Merchandise Store Campaign Analysis

Entrepreneurial Practice: Strategic Analysis, New Venture Development and Professional Reflection

Organisational Strategy and Sustainability: Strategic Evaluation of Engineers & Planners Company Ltd

Business Consultancy Project: Strategic Analysis, Stakeholder Evaluation and Evidence-Based Recommendations

Comparative Analysis of Cultural Factors Shaping Human Resource Staffing Strategies in International Enterprises

Security Evaluation for Connected Systems: IoT Strategy, Secure Design, Security Auditing and Organisational Change

Global Supply Chain Strategy for the Gatwick Airport Northern Runway Expansion

Business Consultancy Project: Strategic Analysis, Stakeholder Evaluation and Evidence-Based Recommendations

Time Series Modelling Case Study: Oil Price Forecasting with ARMA and Alternative Models

Critical Review of Global Logistics: Supply Chain Strategy, Resilience and Sustainability

An Improved Dijkstra’s Shortest Path Algorithm for Sparse Networks

Leading Through Digital Change: Digital Transformation Strategy, Emerging Technologies and Leadership

Digital Forensics Investigation: USB, Memory and Windows Registry Analysis

Modified Merge Sort for Large-Scale Data: Algorithm Analysis, Complexity and Evaluation

AI Innovation Consultancy: Evaluating Artificial Intelligence Solutions for Business Problems

Probability and Statistics Jigsaw Puzzle: Probability Calculations and Chi-Square Analysis in Python

Secure Property Contract Exchange: Cryptographic Protocol Design, Threat Modelling and Post-Quantum Readiness

ParkaLot Enterprise Parking Garage Management System: Software Analysis, Design and Prototype Development

Generative Modelling Case Study: GANs for Medical Imaging, Cybersecurity and Creative AI

Professional Project Portfolio and Strategic Business Presentation

Software Measurement, Goal–Question–Metric Analysis and Process Model Evaluation for DETO