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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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Databases and Business Intelligence
Databases and Business Intelligence – KAP Speciality Chocolates Database Coursewor
This individual coursework for the Databases and Business Intelligence module provides practical experience of database systems through the realistic KAP Speciality Chocolates case study. Students are required to design and implement a relational database solution that supports the management of products, stock, suppliers and purchase orders for KAP Speciality Chocolates Ltd. The case study describes a growing chocolate business with a shop and a storeroom that requires a database system to reduce operational errors and improve stock control. The first task requires students to analyse the case study and identify appropriate entities, attributes, relationships, primary keys, foreign keys and dependencies. Students must produce an extended Entity Relationship Diagram showing how the identified elements should be related. The diagram must include participation and cardinality constraints, and students must clearly document the assumptions made and the notation used. A range of modelling notations and software tools may be used, provided that the required database elements are clearly represented. The second task requires students to translate the ER design into a relational database implementation by writing SQL Data Definition Language statements. The SQL must define suitable tables, attributes, data types, primary and foreign keys and relevant constraints. The chosen data types should be appropriate and foreign-key data types must correspond correctly to their related primary keys. The third task focuses on SQL Data Manipulation Language and requires students to create queries addressing a range of business information needs. These include producing a product price list, identifying purchase orders due for delivery on a specified day, generating shop re-stocking lists, changing product cost and selling prices, identifying products with outstanding purchase-order deliveries, producing a re-order list for products below their minimum warehouse stock level, and identifying suppliers that provide multiple cartons. Students must populate their tables with sufficient suitable data to demonstrate that the SQL works and provide evidence of testing through screen captures of SQL statements and results. The fourth task requires students to demonstrate that the database design is normalised to Third Normal Form (3NF). The normalisation process must begin with unnormalised data and show the stages through First Normal Form (1NF), Second Normal Form (2NF) and Third Normal Form (3NF), explaining the changes and reasons at each stage. The final normalised solution must remain consistent with the ER diagram, assumptions and entity and attribute names used in the database implementation. The final submission must combine all tasks into one report written in English, using Arial 12-point font and single spacing. The report must contain the extended ER diagram and assumptions, SQL table definitions, SQL queries with explanations and testing evidence, and a written explanation of the normalisation process. The completed report must be submitted as a single PDF through SurreyLearn by the specified deadline.
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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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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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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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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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Operating Systems and Networks
2,000 words
Security of Operating Systems and Networks
This individual assignment for the Operating Systems and Networks module focuses on the security of operating systems and computer networks within a business environment. The assessment requires students to produce a professional technical report of approximately 2,000 words, supported by appropriate images demonstrating practical steps and testing activities. The assignment assesses students' knowledge and understanding of operating system and network security threats, vulnerabilities, testing approaches and practical security solutions. It also addresses the ability to develop and write complex scripts to solve problems relating to operating systems and computer networks. The assignment is based on a business scenario involving Net-Tech, a small and medium-sized technology-services enterprise. The organisation is developing a web server to provide its website to customers and is concerned about the security of the proposed system. Key concerns include operating system attacks such as buffer overflow attacks, as well as network threats involving hackers and phishing. Students are required to investigate, design and experiment with the features and functions of a web server and assess the security landscape so that appropriate security requirements can be identified. As part of the practical work, students must create a prototype Net-Tech network test rig. This involves creating two users, including a superuser and a standard user, applying appropriate baseline security, installing relevant software and security tools, conducting security tests and writing scripts to automate repetitive tasks. Students must document assumptions and parameters used in their implementation and may also make recommendations for further security measures and database-driven website functionality. The report covers several stages of the security assessment. The introduction establishes the business scenario, assumptions, aims, objectives, deliverables, available skills and resources, constraints and project scope. The background research examines common vulnerabilities, security threats, risk models, testing approaches and attack or testing tools, together with relevant legal, organisational, ethical, social and professional considerations. The pre-engagement stage focuses on setting up a suitable Linux or Kali Linux testing environment and developing a justified test plan. The engagement stage requires practical investigation of operating-system and network security. Areas include user authentication, file and directory permissions, protection against stack overflow attacks, network weaknesses, operating-system discovery, firewall configuration, listening ports, network statistics, denial-of-service prevention and script-based automation. The final post-engagement section requires students to summarise their work, identify deductions and limitations, propose mitigation measures and recommendations, and provide a self-reflection. The assessment is aligned with learning outcomes relating to understanding network security threats and developing software or scripts to solve problems in operating systems and computer networks. Students are expected to use relevant sources, reference them appropriately and include a bibliography. Practical tools such as Wireshark are specifically identified in the assignment brief, and the work should demonstrate appropriate testing methodology and security practices.
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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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information Governance and Cyber Security
2,500 words
Information Governance Policy for Healthcare Assistant (HCA)
This assessment is the group component of the Information Governance and Cyber Security module and requires a 2,500-word report for the fictional Healthcare Assistant (HCA) organisation. HCA is presented as a large private hospital group operating across the UK, with specialist healthcare services, intensive care facilities and a wide network of GPs, departments, partner hospitals, medical centres and third parties. The organisation processes highly sensitive information including patient personal information, admission details, health records, staff information and other organisational data. These data are shared across different sites and partners and are also used for analytical purposes, treatment planning and marketing activities. The assessment requires students to develop an Information Governance Policy for HCA and provide an accompanying report that justifies the policy contents, selected framework, risk assessment methodology and implementation strategy. The objective is to establish a robust information governance structure capable of protecting HCA's information assets while supporting legal, regulatory and contractual compliance. The first component of the report focuses on the introduction, purpose and scope of the Information Security Policy. Students should establish the organisational context, explain why information governance is important to HCA and define the people, processes, technologies and information assets covered by the policy. Particular attention should be given to the confidentiality, integrity and availability of sensitive healthcare and organisational information. The second component focuses on the identification and allocation of roles and responsibilities. The report should establish appropriate accountability for information governance and information security and consider responsibilities relating to legal, regulatory and contractual obligations. Relevant roles may include senior management, information security leadership, data protection personnel, information asset owners, information asset administrators, employees, contractors and third parties. The third component requires the development of an Information Governance Policy Framework and recommendations for a minimum of eight controls to establish an effective Information Security Management System. The assessment brief identifies ISO/IEC 27001:2022 as an appropriate framework within the developed policy and requires the framework and controls to be justified in relation to HCA's organisational context and security requirements. The fourth component focuses on implementation and monitoring. Students should develop an implementation plan explaining how the information governance policy and security controls can be introduced and maintained. Appropriate monitoring mechanisms should be considered to identify security threats, mitigate vulnerabilities, maintain accountability and support continuous improvement. Overall, the assessment requires a practical and critically justified approach to information governance within a healthcare environment. The report should demonstrate how an effective information governance policy can protect sensitive patient information, support regulatory compliance, establish accountability and strengthen HCA's ability to manage evolving cyber security threats.
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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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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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Network Systems and Administration
2,500 words
Automated Container Deployment and Administration in the Cloud
This assessment focuses on the practical application of network systems administration, cloud infrastructure and automation technologies. The assignment requires students to design and implement an automated deployment process for a server running a Docker container on a cloud platform such as AWS, Azure or GCP. The assessment develops practical understanding of infrastructure automation, configuration management, containerisation and continuous integration and continuous deployment (CI/CD). The project requires the integration of at least two automation tools from technologies such as Terraform, AWS CloudFormation, Ansible, Azure DevOps, GitHub and GitHub Actions. The first stage involves provisioning the required cloud infrastructure, including a server instance, networking components and appropriate security configurations. Students must provide Terraform scripts, CloudFormation templates or equivalent infrastructure-as-code configurations together with an architecture diagram showing the deployed resources. The second stage focuses on configuration management. Ansible or an equivalent automation tool is used to configure the server environment, including installing and configuring Docker and ensuring that the required services start automatically. Students must provide the relevant playbooks or configuration scripts and a README explaining the overall automation flow. The assessment then requires students to containerise a sample web application using a Dockerfile and automate the deployment of the resulting Docker container to the provisioned cloud server. A CI/CD pipeline must also be implemented using Azure DevOps or another suitable CI/CD platform. The pipeline should automatically build and deploy the Docker container whenever changes are pushed to a version-control repository such as GitHub. The final stage requires comprehensive technical documentation and reflection on the complete automation process. Students must document the different phases of deployment, explain the rationale for the selected tools, discuss alternative solutions and identify the challenges encountered and how they were addressed. The final report must include a detailed architecture diagram, a GitHub repository containing the required scripts and configurations, and a working link to a demonstration video of the end-to-end deployment. The technical report should be approximately 2,000–2,500 words and include a title page, summary, introduction, main content, conclusions, references and appropriate appendices. The report should use Times New Roman 12-point font with 1.5 line spacing, clear headings, diagrams or flowcharts where appropriate, and Harvard referencing. The assessment is evaluated through the demonstration, report quality and reusable deployment artifacts, with the marking scheme allocating 40% to the demo, 50% to report quality and 10% to artifacts.
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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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Computing Science
Writing a Literature Review in Computing Science
This individual assessment requires students to write a concise literature review on a selected topic within computing science. The review should be no more than six pages in length and should be written in a style appropriate for a general computing science audience. The assignment is designed to demonstrate technical knowledge, independent learning, effective written communication and professionalism in producing a concise technical document. Students must select a research topic from one of five permitted areas: algorithmic bias and fairness, a data science application, quantum computing, the Internet of Things (IoT), or the use of artificial intelligence in cybersecurity. Possible topics include how algorithms can discriminate and techniques for detecting and correcting algorithmic bias, applications of data science in areas such as agriculture or healthcare, quantum computing algorithms and hardware, technical IoT problems and potential solutions, and the use of AI for cybersecurity threat detection and prevention. The literature review must contain several required components. The first page should contain only the title, student number, abstract and statement of AI usage. The abstract must provide a concise overview of the review and must not exceed 200 words. The report should also include an introduction that provides broad background information before narrowing the discussion to the selected research topic. The introduction should explain why the topic is important and provide relevant context and examples of applications. Students are expected to review a range of relevant literature, including theories, methods, techniques, ethical concerns or tools where appropriate. The selected literature should not simply be described individually; instead, students must synthesise the sources to identify important themes, findings and areas of interest and provide a critical review of the literature. The conclusion should summarise the main findings, identify open issues and discuss possible future directions. The assessment must include a bibliography with accurate and up-to-date references formatted using Harvard style. The final document may be prepared in LaTeX or Word but must use one of the provided templates and be submitted as a PDF through Blackboard. The complete review, including figures and bibliography, must not exceed six pages. The assessment is marked according to structure, sources and their description, synthesis and critical review, and presentation.
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Digital Marketing / Web Design and User Experience
800 words
Digital Marketing Portfolio Website: User Experience, SEO and Professional Digital Branding
This digital marketing assessment requires students to create and launch a fully functional personal portfolio website designed to showcase their professional capabilities, creativity and readiness for employment or client-facing work. The website operates as a digital business card and professional showcase, demonstrating the application of digital marketing strategy, user-centred design, storytelling, usability and digital content creation. Digital Portfolio Website The website must contain a homepage, contact page and portfolio or projects section. The homepage introduces the student and provides an engaging overview of the portfolio, while the contact page includes appropriate professional communication channels such as email or LinkedIn. The projects section must feature approximately three to five digital marketing work samples, which may include mock-ups, content or other digital artefacts. The overall site should demonstrate effective structure, aesthetics, usability and intuitive navigation. Digital Portfolio Website Students must also complete a prescribed LinkedIn Learning course on Wix or WordPress and submit the associated completion certificate. This supports the practical website-development component and demonstrates engagement with contemporary digital-design tools and platforms. Digital Portfolio Website A major component is the reflective rationale, which may be submitted as an 800-word written piece or a four-to-six-minute video commentary. It explains and justifies the design decisions made, the SEO strategies implemented and changes introduced to enhance the user experience. The rationale must be supported by credible sources and demonstrate alignment between theoretical principles and practical design choices. Digital Portfolio Website SEO is explicitly assessed through the effective use of metadata, keywords and image alt text, while design performance also considers originality, calls to action, responsive behaviour, mobile usability and effective use of Wix or WordPress features. The marking structure allocates 20% to website structure and usability, 15% to design and creativity, 15% to SEO, 40% to the reflective rationale, and 10% collectively to the LinkedIn Learning certificate and cover page. Digital Portfolio Website Digital Portfolio Website Overall, the assessment integrates digital marketing, personal branding, web design, UX, SEO, content creation and reflective professional practice. Overview word count: approximately 345 words. AI-use note: this assessment is under Category 1 – Authorised use of AI. AI may be used within platforms such as Wix or WordPress to help create the portfolio, but AI must not be used to write the reflective rationale, which must be composed entirely by the student. Digital Portfolio Website
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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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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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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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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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Network Systems and Administration / Cloud Computing / DevOps
2,500 words
Automated Container Deployment and Administration in the Cloud
This practical Network Systems and Administration assessment requires students to design and implement an automated cloud deployment workflow using modern DevOps and infrastructure automation technologies. The overall objective is to deploy a cloud-hosted server running a Docker container while integrating at least two automation tools such as Terraform, AWS CloudFormation, Ansible, Azure DevOps, GitHub Actions or GitHub. Students may use a cloud platform such as AWS, Microsoft Azure or Google Cloud Platform. B9IS121 Network Systems and Adm… The first stage focuses on cloud infrastructure provisioning. Students automate the creation of a server instance, such as an AWS EC2 instance or Azure virtual machine, and configure supporting infrastructure including networking and security groups. Infrastructure must be provisioned through tools such as Terraform, GitHub Actions or AWS CloudFormation. The required outputs include reusable infrastructure scripts or templates and an architecture diagram showing the deployed cloud resources. B9IS121 Network Systems and Adm… The second stage addresses configuration management. Students use Ansible or an equivalent automation platform to configure the provisioned server, install Docker and ensure Docker starts automatically when the server boots. Deliverables include Ansible playbooks or equivalent configuration scripts together with a README file explaining the automation workflow. B9IS121 Network Systems and Adm… The third stage requires students to containerise and deploy a web application. A Dockerfile must be created for either an existing or newly developed sample application, and deployment of the resulting container must be automated on the provisioned server. The required artefacts include the Dockerfile, deployment scripts and application repository. B9IS121 Network Systems and Adm… Students must also create a CI/CD pipeline using Azure DevOps or another suitable CI/CD platform. The pipeline should automatically build and deploy the Docker container whenever new code is pushed to a version-control repository such as GitHub. Students must provide the relevant pipeline configuration, normally in YAML, and demonstrate the pipeline operating successfully. B9IS121 Network Systems and Adm… Documentation is an important part of the assessment. Each student produces an independent PDF report explaining every stage of the automation process, challenges encountered and how those challenges were resolved. A 10-minute walkthrough video must demonstrate the complete end-to-end deployment, and the report must contain a detailed architecture diagram. B9IS121 Network Systems and Adm… The technical report should include a title page, summary, introduction, main technical content, conclusion, references and appropriate appendices. Students are expected to justify the tools selected and critically discuss alternative solutions, advantages and limitations. The report is expected to contain approximately 2,000–2,500 words and should use clear headings, diagrams or flowcharts where relevant, and academic or professional sources such as journal articles, whitepapers, DevOps documentation and industry reports. B9IS121 Network Systems and Adm… B9IS121 Network Systems and Adm… The marking scheme allocates 40% to the demonstration, 50% to report quality and 10% to technical artefacts. Higher-performing submissions are expected to show a working deployment, clear justification of technical actions, strong understanding of automation tools, professional report structure, consistent referencing and reusable scripts that reproduce the same deployment results. B9IS121 Network Systems and Adm… The final submission includes a comprehensive PDF report of approximately 5–8 pages, a detailed README, and links to the relevant scripts, configurations and deployment evidence. B9IS121 Network Systems and Adm…
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Web Applications / Artificial Intelligence / Software Development
Smart Clinic Appointment and Patient Management System with AI-Based Demand Prediction
This Web Applications and AI coursework requires students to design, implement and evaluate a Smart Clinic Appointment & Patient Management System for a small healthcare clinic. The application combines conventional web-development functionality with an artificial-intelligence component for predicting appointment demand. The system is expected to use Java EE technologies, including Java Servlets, JSP, Web Services and JDBC, together with a relational database such as MySQL or PostgreSQL. f3855340dabd17407efd386c38cfdc3… The patient-facing side of the application should allow users to browse and search clinic services by department or specialty, price, availability and duration. Patients must be able to view detailed service information, select a clinician where appropriate, choose an available date and time, enter their details and confirm an appointment. The system should also provide a booking reference and basic appointment-history functionality. f3855340dabd17407efd386c38cfdc3… The administrative interface focuses on operational management. Staff should be able to add, update and remove services, configure consultation duration and pricing, manage clinician working hours and appointment-slot availability, and generate basic reports. f3855340dabd17407efd386c38cfdc3… A separate machine-learning component requires students to implement appointment-demand prediction using WEKA regression embedded in Java. The provided sample dataset contains Year, Month, Promotions Cost and Booking Requests. Students must expand this dataset to at least 60 realistic rows, including seasonal changes and plausible variation in marketing expenditure and demand. A regression model is then trained to predict booking requests for the following year based on promotional spending, including estimation of future demand if promotions expenditure increases by 10%. f3855340dabd17407efd386c38cfdc3… The assessment also requires evidence of professional software-development practice. Students must provide application-design artefacts such as design patterns, ER diagrams, wireframes and sketches, document the development process, demonstrate correct use of JSP, Servlets, Web Services and JDBC, and provide evidence of implementation through code, database content and screenshots. Regular GitHub commits are required to demonstrate ongoing development. f3855340dabd17407efd386c38cfdc3… f3855340dabd17407efd386c38cfdc3… The final submission includes a DOCX or PDF report containing system-design and implementation information, links to a private GitHub repository and a demonstration video of no more than five minutes. The assessment is classified as Green for AI use, meaning AI tools may support tasks such as generating example datasets, suggesting code snippets and brainstorming features or tests, provided their use is clearly declared in the report. f3855340dabd17407efd386c38cfdc3… Overall, the coursework integrates full-stack Java web development, relational database design, web services, software engineering and machine-learning regression within a healthcare appointment-management scenario. Important: the uploaded brief states that it is for Coventry University Group students' own use and must not be passed to third parties or posted publicly. f3855340dabd17407efd386c38cfdc3… So for a public Reference Library, use an original summary like the one above rather than publishing the original brief itself.
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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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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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Cyber Security / Penetration Testing
Web Application Penetration Testing and Security Vulnerability Assessment Portfolio
This postgraduate cyber security portfolio requires students to conduct a structured penetration test of a controlled web application and document the technical findings in a professional security-testing format. The assessment develops practical competence in identifying, validating and communicating security vulnerabilities while maintaining appropriate legal, ethical and professional boundaries. Assessment Brief CMP-L021 (PG) … Students begin by performing network and service enumeration, identifying open ports and the services running on the target host. They are expected to interpret the security implications of the findings and provide appropriate recommendations to a hypothetical client. The assessment then progresses into web-application vulnerability testing using tools such as a web browser, Burp Suite Community, Nmap and student-developed scripts. Assessment Brief CMP-L021 (PG) … A major part of the portfolio examines common web-security weaknesses including SQL Injection and Cross-Site Scripting. Students must demonstrate how they tested the application, capture relevant requests and responses, and explain the evidence supporting their conclusions. Additional tasks involve application and server reconnaissance, including identification of technologies, server versions, publicly exposed files and other information that may create security risks. Assessment Brief CMP-L021 (PG) … The higher-level reporting component requires students to document significant vulnerabilities using the conventions of a professional penetration-test report. This includes assigning CVSS scores, relating identified weaknesses to the OWASP Top 10 and NIST classifications, and supporting findings with appropriate technical evidence. Assessment Brief CMP-L021 (PG) … Students must also produce an executive summary for a non-technical audience, considering security, privacy, regulatory exposure and budget implications. A vulnerability table linking technical weaknesses with relevant regulatory concerns is also required. Overall, the assessment integrates technical penetration testing with risk communication, vulnerability classification, evidence collection and professional security reporting. Assessment Brief CMP-L021 (PG) … Overview word count: approximately 320 words. AI-use note: AI can be used in this assessment, but any use must be acknowledged and AI-generated outputs must be appropriately cited. Assessment Brief CMP-L021 (PG) …
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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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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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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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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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Engineering and Environment Advanced Practice
3,000 words
AP Research Project – Reflective Individual Report and Poster Presentation
This assessment is the Advanced Practice (AP) Research Project for the Engineering and Environment Advanced Practice London Campus Research Project module. It is designed for postgraduate students undertaking an independent research project with supervisory guidance. The assessment provides an opportunity to reflect critically on the research process, knowledge gained, professional development and challenges encountered during the project. Students are expected to demonstrate independent learning, research skills, critical thinking and the ability to communicate complex ideas in a professional context. The main assessment is a 3,000-word Reflective Individual Report, which contributes 80% of the module assessment. The report is structured around four key areas. The first section, Finding a Research Topic, requires students to explain how and why they selected their research topic, the research tools and search strategies used, the library collections explored, their research aims and objectives, and relevant discussions or recommendations received from their supervisor. The second section, Professional Activities, focuses on reflection on research development activities, scheduling, the independent researcher role, challenges such as time management, and communication with the supervisor. The third section, Literature Review and Research Work, requires students to critically review relevant literature, discuss their research method, demonstrate major research activities and consider the feasibility of the selected method, including challenges and recommendations. The final section, Reflection of Research Project, requires critical reflection on personal strengths and weaknesses, continuous self-development and the relevance of research activities to the student's programme of study and future career. Areas such as decision making, problem solving, communication and influencing, technical skills, collaboration, innovation and proactivity should be considered. The second component is a 10-minute Poster Presentation worth 20% of the assessment. The poster should provide a balanced combination of visuals and text and present the research objectives and significance, a summary of the literature review and research method, key research findings, and conclusions and recommendations. The assessment also requires appropriate academic presentation, including a cover page, table of contents, page numbers, figure and table captions, numbered headings and consistent formatting. Harvard or APA referencing may be used. The report is submitted through Turnitin and is subject to anonymous marking. The assessment is a Pass/Fail module, with students required to achieve at least 50% to pass.
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Cyber Security
Contextual Risk Assessment and Policy to Address Information Security within Supplier Agreements
This assignment focuses on the development of a contextual risk assessment and an information security policy addressing security requirements within supplier agreements for Heathrow Airport Holdings (LHR). The assessment is an individual postgraduate task worth 60% of the module and requires students to apply information security risk assessment methods, security standards and policy development techniques to a realistic organisational scenario. The assignment is based on a cyber-attack affecting Heathrow and other European airports in September 2025, where disruption to a third-party cloud-based check-in and baggage system affected airport and airline operations. The scenario highlights the security risks associated with interconnected systems, third-party suppliers and dependence on critical digital services. Students are required to assume the role of a new Chief Information Security Officer (CISO) at Heathrow Airport Holdings and investigate the organisation, its environment and the relevant threat landscape. The task requires the development of a clear organisational context, including appropriate assumptions, followed by an asset-based information security risk assessment. The risk assessment should identify and prioritise relevant risks and support the selection of controls needed to manage residual information security risks. The main policy component requires students to develop an “Information Security within Supplier Agreements” policy aligned with the ISO 27000 family. The policy should establish clear security responsibilities between LHR and its suppliers and address the protection of information assets, legal and regulatory requirements, and supplier-related security obligations. Particular attention is required for confidentiality, integrity and availability, together with ISO 27002 controls relating to information security policies and supplier agreements. The assignment also requires consideration of acceptable use of information and other assets, information classification and information labelling. The final submission consists of a cover page, context establishment, an asset-based risk assessment, the supplier information security policy, references and supporting appendices. The context establishment is limited to a maximum of two pages or 1,000 words, while the policy is limited to three pages or 1,500 words. The risk assessment is completed using the supplied template. Students are also required to provide evidence and commentary concerning the development and tailoring of the policy when using an approved AI tool, together with a self-written evaluation addressing strengths, weaknesses, privacy, GDPR and ethical considerations. The assessment is marked across context establishment, asset-based risk assessment, the information security within supplier agreements policy, and presentation, design and references. At least 20 authentic references, including standards and papers accessed through the University library, are required.
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Environmental Sustainable Engineering
3,000 words
Environmental Sustainable Construction & Logistic Sources – EG7037
This coursework assesses Environmental Sustainable Engineering and Logistic Sources through a large-scale construction project scenario. The student is appointed as the project manager for a £320 million design-and-build project involving the development of a new shopping centre in central London. The project is planned over a 48-month period and is presented as a flagship initiative focused on environmentally friendly and sustainable construction practices, with government support for its sustainability commitments. The project manager is responsible for protecting the client's interests while ensuring that project standards, schedules, budgets, procurement requirements and quality expectations are achieved. The assignment is structured around environmental sustainability, construction logistics, procurement, renewable energy, health and safety, and sustainable design. Part A requires investigation of the environmental, economic, historical and cultural factors that could contribute to significant project costs and delays. It also requires discussion of four renewable or sustainable energy sources that could be used within the project, together with justification for each selected energy source. These activities require consideration of the project's location, sustainability objectives and practical construction requirements. Part B focuses on supply chain management and health and safety. Students must outline the supply chain management and procurement process for the material resources required for the construction project. This includes consideration of how appropriate materials and suppliers can be sourced and managed. The section also requires identification of key health and safety considerations during the production phase and discussion of the associated risks. Part C focuses on sustainable design systems. Students must discuss the need for implementing passive or active systems during the design stage and identify appropriate tools or techniques that can support their application. The potential environmental impacts of these systems must also be considered. The assignment therefore requires students to connect sustainable design decisions with environmental performance and the wider objectives of the construction project. The completed coursework should be approximately 3,000 words, excluding appendices and labelled diagrams or sketches. Students are expected to provide a well-researched and clearly structured written account using appropriate textbooks and other relevant sources. Images, photographs and diagrams should include captions and be cross-referenced within the text. The submission should include a conclusion and a properly cited bibliography or reference list. References must follow the Cite Them Right requirements. The coursework is submitted electronically through the designated Turnitin link.
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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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Digital Marketing
Three Weekly Digital Marketing Tutorial Challenges
This assessment consists of three weekly digital marketing tutorial challenges designed to develop practical skills in digital marketing, consumer insights, content creation, inclusive communication, ethical storytelling and campaign design. The assessment accounts for 45% of the module and requires students to apply digital marketing theory and consumer insight techniques in real-world marketing contexts. The activities are completed through tutorial-based learning, where students participate in discussions, receive tutor guidance and develop their work before submitting it through Canvas. The assessment focuses on applying consumer insights, data analytics tools and digital marketing strategies to create meaningful and responsible customer experiences. Challenge 1, titled “Are You Being Inclusive?” – Brand Audit & Persona for Ethical Reach, focuses on ethical digital auditing and inclusive persona design. Students select a brand from their home country and evaluate the inclusiveness and accessibility of its digital marketing across its website, social media and paid advertising. They then develop two to three detailed customer personas representing underserved or marginalised customer groups. Students also use AI analytics tools such as Google Trends, SparkToro or simulated AI insights to identify audience behaviours and preferences. The challenge is linked to SDG 10 – Reduced Inequalities and includes consideration of the ethics of using AI in digital marketing and its effect on the credibility of consumer insights. Challenge 2, titled “Don't Just Capture Attention – Respect It” – Campaign Idea Pitch, focuses on sustainable branding and growth. Students research the client's existing branding, examine opportunities to expand or sustain its audience and use consumer insight tools such as Google Trends, reviews and surveys to understand public perceptions. Students then create a visual mini-campaign promoting sustainable and transparent brand messaging, including social media content and AI-generated visuals. The campaign is connected to SDG 16 – Peace, Justice and Strong Institutions. Challenge 3, titled “Create, Educate, Disseminate & Evaluate”, develops digital social marketing and consumer engagement. Students extend the campaign developed in Challenge 2 into an interactive digital event that promotes positive behavioural change and educates audiences about a social issue. The activity must consider audience interests, increase interactivity and engagement, and provide evidence of positive engagement. This challenge is linked to SDG 4 – Quality Education. Overall, the assessment develops students' ability to combine digital marketing strategy, consumer insights, ethical considerations, sustainability and creative campaign design in practical marketing activities.
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Engineering and Environment Advanced Practice London Campus Research Project
3,000 words
LD7152 – AP Research Project
The LD7152 AP Research Project is a postgraduate research and reflective assessment for students studying within the MSc Computing Framework or MSc International Project Management programme. The module focuses on developing students as independent researchers and requires them to reflect critically on their research strategy, activities, learning and personal development. The assessment is designed to encourage students to recognise their achievements, identify challenges encountered during the research process and evaluate how their research experience has contributed to their academic and professional development. The assessment consists of two components: a 3,000-word Reflective Individual Report worth 80% and a 10-minute Poster Presentation worth 20%. Students are expected to work independently while receiving supervisory guidance. The reflective report requires students to demonstrate critical engagement with knowledge discovery and reflect on their educational development in relation to the challenges experienced during their research project. The report is structured around four main areas. The first section, Finding a Research Topic, is approximately 500 words and requires students to explain their chosen topic, why it was selected, the research tools and search techniques used, the Library collections explored, the research aims and objectives, and relevant discussions or recommendations from their supervisor. The second section, Professional Activities, is approximately 500 words and focuses on research development tasks, scheduling, the independent researcher role, challenges such as time management, and communication with the supervisor. The third section, Literature Review and Research Work, is approximately 1,500 words. It requires a critical review of relevant literature with appropriate citation, discussion of the research method and major research activities, and consideration of the feasibility, challenges and recommendations associated with the selected method. The fourth section, Reflection of Research Project, is approximately 500 words and focuses on achievements, contributions, strengths and weaknesses, continuous self-development and employability. Students are expected to reflect on areas including decision making, problem solving, communication and influencing, technical skills, collaboration, innovation and proactivity. The second assessment component is a 10-minute poster presentation. The poster should provide an overview of the research activities and communicate what the student learned during the research process. It should balance visual and textual information and include the research objectives and significance, a summary of the literature review and research method, key research findings, and conclusions and recommendations. The report must include a cover page, table of contents, page numbers and captions for figures and tables. The required formatting includes Times New Roman, 12-point font, numbered headings and approximately 1.2–1.3 line spacing. The assessment brief permits Harvard or APA referencing. The report is submitted electronically through Turnitin on Blackboard. The module is assessed on a Pass/Fail basis, with students required to achieve 50% or above to pass. The assessment also evaluates critical reflection, application of knowledge, independent learning, communication of complex ideas, personal development and reflection on technical leadership.
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Data Mining
Data Mining – Classification, Model Optimisation and Evaluation
This individual Data Mining assignment requires students to apply the techniques covered in the module using the WEKA data mining platform. The assessment is worth 40% and focuses on practical application of machine learning and data mining methods, requiring students to configure algorithms, analyse datasets, optimise model parameters, evaluate classification performance and explain their technical choices and results. The assignment also assesses the ability to critically evaluate different algorithms and models of data mining. The assignment includes several tasks covering different stages of the data mining process. Students are required to work with supplied datasets and use appropriate preprocessing and classification techniques. The datasets include a balanced screenshot dataset containing processed screenshots classified into categories such as "Okay" and "Bad", where the objective is to train a model capable of identifying inappropriate content. The data has been processed using PCA to provide a smaller four-dimensional representation while protecting privacy and reducing the size of the data. Another supplied dataset concerns furniture reviews, containing positive ("pos") and negative ("neg") written feedback, with the objective of building a model that can determine whether a furniture review belongs to either class. The assessment evaluates students' ability to understand and describe the datasets, including the number of instances, number of columns, data types and relevant statistical information. For text-based data, students must apply appropriate vectorisation and describe the resulting dataset characteristics. Students must also consider class imbalance and apply an appropriate method where necessary, explaining how the chosen approach affects the distribution of instances between the classes. A significant component of the assignment involves classification algorithms and parameter optimisation. The assessment requires students to work with algorithms including Naive Bayes, LibSVM and J48. Students must investigate appropriate parameters and perform parameter searches or fine grid searches to identify suitable configurations. They must explain the selected parameters, their impact on the model and the reasoning behind the chosen values. Model performance must be evaluated using appropriate validation techniques, including cross-validation. Students are required to compare the algorithms using results such as overall accuracy and confusion matrices. The assignment expects students to identify an appropriate or best-performing algorithm in the context of the dataset and to provide a clear explanation of the comparison rather than simply reporting numerical results. The rubric places emphasis on accurate configuration, clear explanation of parameter choices, dataset analysis, class-balance treatment, parameter optimisation, cross-validation and critical comparison of algorithm strengths and weaknesses. High-quality work should explain both the technical process and the implications of the results, with results presented clearly through appropriate tables, confusion matrices and graphical outputs where required. The submission must be a single PDF document containing the report and must not exceed 10 pages. Students are instructed to include their student ID at the beginning of the report but not their name or other identifying details so that marking remains anonymous. Screenshots are specifically required to demonstrate use of the student's ID number as the random seed; other WEKA results should be presented in the student's own tables or result formats. The brief also states that no research beyond the material covered in the module is required and therefore no citations or reference list are required. The assignment explicitly prohibits the use of Generative AI tools for creating content and prohibits using GenAI tools or proofreading services for proofreading. Students are expected to complete the practical work themselves and explain their own technical choices and results.
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Networking and Security Practice
Networking and Security Practice – Recorded Demonstration
This assessment for the MSc Cyber Security module Networking and Security Practice is a practical recorded-demonstration coursework designed to assess students' ability to configure, secure, troubleshoot and monitor a virtualised sandbox network. The assessment contributes 60% of the module mark and consists of four recorded demonstration videos, with each video limited to a maximum of five minutes. The completed videos are submitted through a Moodle quiz as video files or accessible links. The practical environment uses virtual machines running Ubuntu Server and Ubuntu Desktop on VirtualBox or UTM. Students deploy a four-machine architecture consisting of a Gateway, Webserver, Workstation and Zabbix-Server. The Gateway acts as the router, firewall and NAT gateway; the Webserver hosts an Nginx web server; the Workstation is used for administration and testing; and the Zabbix-Server provides network monitoring. The architecture requires appropriate network interfaces, IP addresses, routing and communication between the different internal networks. The coursework develops practical networking and system administration skills through several phases. Students install and configure operating systems, allocate virtual machine resources, configure static IP addresses, enable IP forwarding and NAT masquerading, and implement firewall rules using iptables. They also develop command-line proficiency using networking, DNS, security, remote-access and web tools including ping, traceroute, ss, nslookup, dig, nmap, Wireshark, netcat, SSH, SCP, rsync, curl and wget. Students must also configure secure remote access and deploy an Nginx web server. SSH must be hardened by disabling password authentication and root login, while key-based authentication is used for secure access. The Webserver must contain a customised landing page showing the student's name and student ID, which is accessed from the Workstation. The monitoring component requires installation and configuration of Zabbix, deployment of agents across the virtual machines, host monitoring, a customised dashboard containing at least five live-data widgets and configured alerts or triggers. Students must explain what their selected monitoring elements measure and why they are operationally useful. The traffic-analysis component uses Wireshark to capture and examine HTTP, ICMP and DNS traffic. Students apply appropriate filters, identify protocols using the Protocol Hierarchy and discuss the security implications of unencrypted HTTP traffic, including secure alternatives such as HTTPS and DNS over TLS. The security-evaluation component uses Nmap within the isolated virtualised sandbox to identify open ports and services, assess vulnerabilities and recommend mitigations. Students must also demonstrate iptables forwarding and NAT masquerading rules. The four videos cover Network Infrastructure, Network Monitoring, Traffic Analysis and Security Evaluation. The assessment is marked out of 100, with 35 marks allocated to Network Infrastructure, 25 to Network Monitoring, 20 to Traffic Analysis and 20 to Security Evaluation. Students are expected to provide clear voice narration, explain commands and outputs, demonstrate technical understanding and critically relate their work to network security. The assessment develops employability skills in Linux administration, remote system management, network troubleshooting, security hardening, packet analysis, port and service scanning, virtualisation and network monitoring. It also requires students to conduct security testing ethically within their own isolated virtualised environment and prohibits unauthorised scanning of university networks, public websites or other systems.
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Principles of Data Science
3,000 words
Principles of Data Science – Predictive Modelling and Data Analysis
This individual assessment for the Principles of Data Science module requires students to select, apply and critically evaluate data science methods, tools and techniques using one of three provided datasets and its associated scenario. The main assessment takes the form of a 3,000-word report in which students explore their chosen dataset, identify an appropriate predictive modelling approach, build and evaluate models, interpret the findings and critically reflect on the overall process and outcomes. The assessment addresses the principles and foundations of data science, statistical methods, data preparation, visualisation, predictive modelling, decision making and the critical evaluation of data science techniques and tools. Students begin by exploring the selected dataset to understand its structure, characteristics and limitations. Although the supplied datasets have already been cleaned, students may undertake additional data preparation or transformation where necessary. Any preprocessing decisions must be justified in relation to the requirements of the selected analytical methods. Feature selection should also be considered as part of preparing the data for model development. The assessment requires students to identify suitable forms of analysis for the selected scenario and justify their choice of methods. At least two different techniques must be used to develop models with predictive capacity for the response variable in the chosen dataset. The models must be trained and tested consistently, using the same training and test datasets so that their performance can be compared fairly. Where appropriate, students should also provide insight into feature importance and explain the contribution of relevant variables to predictive performance. Model performance must be evaluated using suitable metrics, followed by a clear description of the findings and recommendations appropriate for the intended audience. The report should document the complete analytical workflow, including data exploration, preprocessing, feature selection, model development, testing and evaluation. Students are expected to explain and justify the decisions made throughout the process rather than simply presenting code or model results. The assessment also requires students to demonstrate practical proficiency in data science tools and techniques. The brief expects the use of R for completing the assignment and requires evidence of important elements of the code, although the complete code does not need to be submitted. Data visualisation must be used to support the written discussion and communicate relevant findings effectively. The assessment is evaluated across theoretical knowledge and method selection, data exploration and processing, technical application and model evaluation, communication of findings, and overall presentation and referencing. The assessment therefore combines technical implementation with critical analysis, requiring students to explain why particular methods were selected, evaluate their effectiveness and consider the limitations and implications of the resulting findings. A separate second assessment component accompanies the written report. This component requires a presentation of the key findings from the written work using a maximum of five slides and a presentation duration of no more than seven minutes. It should summarise the dataset, methods, key findings and project outcomes while providing critical reflective commentary on lessons learned, factors affecting success and potential real-world applications.
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Programming for Data Science
2,500 words
Individual Coursework – Programming for Data Science
This Individual Coursework assignment for the Programming for Data Science module requires students to demonstrate practical programming skills and the ability to critically select and apply Python data science tools and libraries. The assessment is worth 20 credits and has a word count of 2,500 words plus 10%, excluding the reference list and output. Students are required to submit one clearly organised report covering two tasks and their individual subtasks. Task 1 focuses on designing, building, testing, explaining, adapting and critiquing a Python program. Students are required to implement a dice-based football match simulation for two players using at least two Python functions. The implementation should follow the logic of the physical dice game, demonstrate good Python coding style, and use functions designed with high cohesion and low coupling. The report must include the full Python code and carefully selected output from a sample match that demonstrates the progression of the game and changes in the score. Students must not implement a Python class or graphical visualisation. The second part of Task 1 requires students to explain how they designed their implementation, including assumptions, incremental development and testing. They must then modify their program to estimate at least two performance measures relevant to a football manager. The coursework asks students to investigate how these measures change when a restrictive shot clock is introduced and to model a realistic “Hail Mary” shot when the shot clock is close to expiring. Students must provide modified Python code, clearly identify the changes made, include selected output for checking the logic, and provide a robust conclusion based on comparison of the results. Task 2 focuses on critically assessing, selecting and applying Python data science libraries and algorithms. Students must describe an applied data science problem involving unstructured data such as image, audio, video or text. They must provide a specific example based on the context of a Coventry University fresher and explain how the problem could be solved manually. Students then select two Python libraries, justify their selection, compare their capabilities, apply both libraries to the chosen problem, and provide the relevant Python code and output. The final part of Task 2 requires a critical assessment of the selected Python libraries using the student's experience and additional sources. Factors may include coding difficulty, adaptability, level of control and quality of the resulting solution. Students must make a reasoned assessment of the suitability of the libraries for their chosen application and support their discussion with appropriate references. The assignment assesses three module learning outcomes: understanding essential programming concepts relevant to data science; designing, building, testing, explaining, adapting and critiquing small programs in a high-level programming language; and critically assessing, selecting and applying data science tools, libraries or algorithms for different applications and tasks. The submission must be provided as a single Microsoft Word or PDF report, organised by subtask, with each task starting on a new page. Python code, relevant output and plots must be included directly in the report. The brief requires APA referencing and states that sources should be cited in-text with a reference list for each task where relevant.
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Security of Emerging Connected Systems
1,500 words
CW1: Policy and Legal Aspects Report – IoT System
This 1,500-word report for the Security of Emerging Connected Systems module examines the legal and security implications of a proposed Internet of Things (IoT) system designed for consumers to monitor food intake and bodyweight. The coursework requires students to provide an initial investigation of the potential legal pitfalls associated with the proposed product and identify appropriate solutions or mitigation measures. The report is worth 5 credits and is assessed as an individual written report. The proposed IoT system consists of several connected components. A smartphone application allows users to scan barcodes of processed food to record calorie and nutritional information against their health record. A kitchen scale communicates with the phone application to record the weight of ingredients used in home-cooked meals. A bathroom scale records the user's weight and provides light and sound reminders to encourage regular measurements. A UK-based server stores the collected information and generates individual user reports. The main purpose of the report is to ensure that the company understands the UK and international laws that may apply to the proposed system. Students must identify potential legal issues and recommend appropriate mitigation through technology, organisational policy, licensing arrangements or user agreements. The system definition is deliberately broad, so students should not make unsupported assumptions about its design. Where several options have different legal implications, the report should compare the relevant alternatives and explain their implications rather than presenting only one solution. The initial product is intended for UK residents, while the company is considering future expansion into the United States. Consequently, the report should focus primarily on UK law but also include a short section discussing legal aspects that may need to be reconsidered when entering the US market. The report is intended for company executives and may subsequently be provided to the R&D department. Therefore, high-level outcomes should be communicated early, while useful links to technical information such as encryption schemes, protocols and frameworks may be provided without extensive technical explanations in the main report. The assessment places 50% of the marks on understanding and coverage of UK and US law, 40% on technical recommendations and 10% on report presentation. Strong submissions are expected to provide comprehensive coverage of relevant legislation, connect legal issues with the wider security context, analyse technical recommendations for both regions, identify differences between UK and US requirements and support arguments with appropriate citations and a wide range of sources. The assignment learning outcomes focus on critically evaluating the role of security policy in protecting information assets and proposing appropriate policies for internet-based technologies. They also require students to demonstrate an understanding of key legislation relating to information security and how legislation influences organisational security policy. The final report should therefore combine legal analysis with practical security recommendations, addressing the proposed IoT system from both UK and US perspectives while remaining suitable for both technical staff and non-technical management.
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Corporate Strategy
4,000 words
Strategic Case Study – Corporate Strategy
This Corporate Strategy assessment requires students to undertake a critical strategic analysis of a chosen organisation and develop evidence-based recommendations for its long-term growth and competitive position. The assignment is presented as a 4,000-word Strategic Case Study and focuses on analysing practical business situations through the application of corporate strategy theories, analytical tools and strategic frameworks. The assessment aims to develop students' ability to evaluate an organisation's competitive advantage, identify significant strategic challenges and opportunities, and propose practical strategies for sustainable growth. The report begins with an introduction explaining the purpose of the case study and identifying the selected company. The strategic positioning section then examines the organisation's current competitive advantage, differentiation from competitors, fundamental competencies and resources. Relevant theories and strategic frameworks should be applied to support the analysis. The external environment section requires a critical evaluation of industry attractiveness using Porter's Five Forces. Students must also examine the factors driving organisational change, compare the selected organisation with close rivals and provide strategic recommendations for addressing identified challenges. The international strategy section critically analyses the effectiveness of the company's existing international expansion strategy and requires students to propose a new expansion strategy for a geographical location in an international market. An appropriate internationalisation theory and market-entry mode should be applied to support the proposed strategy. The challenges and opportunities section examines major issues affecting the organisation, including areas such as market competition, technological disruption and regulatory change. Students must identify opportunities that could strengthen the company's competitive position and use an appropriate framework to consider the development, leadership and implementation of organisational change. The proposed leadership-driven strategy should also be reflected upon in relation to the company's strategic goals. The final main section provides two to three actionable strategic recommendations that the organisation should implement to sustain or enhance its competitive advantage. Students are also required to include an appendix of no more than 500 words containing concise explanations, models or frameworks demonstrating their understanding of theories and concepts relevant to the assessment. The appendix should support the main analysis and be clearly referenced within the report. The assessment develops several strategic management capabilities. The assessed learning outcomes include critically analysing a company's strategic position using analytical tools and theoretical frameworks; developing corporate-level strategies and considering their implementation and control; integrating innovative and sustainable practices into strategic planning; and using performance measurement instruments to assess strategic initiatives. The brief also aligns with CMI Level 7 Strategic Management and Leadership Practice units covering strategy development and strategic change. The submission is an individual written coursework assignment submitted through Turnitin. The written assignment must be submitted as a Microsoft Word document rather than PDF. Students must acknowledge and reference any AI tools used in developing the assignment and provide appropriate acknowledgement of all sources.
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Entrepreneurial Practice
3,500 words
Entrepreneurial Practice – Critical Analysis, Business Venture Proposal and Reflective Practice
This assessment for the Entrepreneurial Practice module requires students to critically analyse a real organisational issue using one of three specified employer case study videos and develop a proposal for a new business venture. The assessment is an individual 3,500-word equivalent portfolio consisting of three tasks: a 1,500-word report, a 1,000-word briefing note, a narrated two-slide PowerPoint presentation, and a 500-word reflective personal and professional account. Students must select only one of the three case studies provided: Paragon, Reliance Housing, or Ovo Biomanufacturing. The chosen case study must be used consistently across the relevant tasks. Task 1 requires a short report based on the selected employer case study. Students must critically and strategically analyse the challenges and issues facing the organisation using one or more appropriate strategic analysis tools. The report must also critically evaluate the organisation's leadership model or models and communication strategies, including their impact on employee and organisational culture and performance. Finally, students must provide three justified recommendations designed to enable and improve organisational performance. This section is 1,500 words and represents 30% of the assessment. Task 2A requires a 1,000-word briefing note based on the same case study. It involves a critical appraisal of the phases of entrepreneurial practice from the idea stage through to delivery, including the benefits and potential funding sources for the proposed new business venture. Students must also critically analyse strategies for addressing and managing risks within the proposed venture and critically appraise the entrepreneurial traits, characteristics, skills and competences required for strategically positioning the new venture within the organisation. Task 2B requires a two-slide narrated PowerPoint presentation lasting three minutes. The presentation should pitch the proposed business idea to an audience of employees, managers, senior managers and the Board of Directors within the case study organisation. It should explain what informed the new business idea, its benefits to the organisation, potential funding prospects, risks and risk-management strategies, and the entrepreneurial traits, characteristics, skills and competences required for strategic positioning. Task 3 is a 500-word reflective personal and professional account. Students must select a professional area from the CMI Code of Conduct and Practice and reflect on how it can be applied to their current or future professional career. The brief allows the use of reflective models such as Gibbs, Kolb, Rolfe or Burton, or another appropriate professional and systematic reflective model. The assessment develops skills in communication, creative thinking, integrity, adaptability and completing tasks, with particular emphasis on leadership and entrepreneurial skills. The learning outcomes include evaluating ethical and inclusive approaches to leadership, diversity and entrepreneurship; reflecting critically on entrepreneurial practice and effective leadership; understanding principles for leading and developing people; understanding leadership and development strategy; and understanding entrepreneurship and entrepreneurial practice in strategic contexts. The submission requires Task 1, the Task 2A briefing note and Task 3 to be combined into one MS Word document, while Task 2B must be submitted separately as a narrated PowerPoint with audio. The written work should include a cover sheet, page numbers, Arial 12-point font and 1.5 line spacing. References and appendices are excluded from the word count, while words in tables count towards the final word count. The assessment also carries a 10% allocation for referencing and structured presentation across the three tasks. The assignment brief places particular importance on using the selected case study as the foundation for the analysis. Wider research may be used, but the primary focus should remain on the case study interview, CMI materials, module-related models and content. Students are expected to apply relevant models, tools and methods discussed in seminars and CMI learning journeys and support their analysis with appropriate evidence and academic literature.
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Network Security
1,500 words
The Case Study – Network Security Planning and Upgrade
This individual assessment for the Network Security module requires students to work as network consultants and carry out network and security planning and an upgrade for an imaginary company. The assignment is titled “The Case study” and requires students to produce a written report presenting solutions to the problems identified within the case study. The assessment is worth 15 credits and requires approximately 1,500 words, with a permitted variation of ±10%. The coursework focuses on applying network security concepts and protocols to contemporary Internet and mobile-based solutions and technologies. Students are expected to analyse the requirements of the imaginary organisation, identify relevant network and security issues and propose appropriate planning and upgrade solutions. The report should demonstrate an understanding of network security technologies while considering the organisation's information assets and operational requirements. A significant part of the assessment concerns network performance. Students must provide recommendations and suggestions for addressing network performance issues identified in the case study. Where the proposed solution changes the existing network design, an appropriate network diagram should be included. The brief allows students to use tools such as Packet Tracer or other suitable applications to represent the proposed network design. The assignment also requires students to consider security policy and network protection. The existing security policy should be reviewed and recommendations should be made for improving it. Students are specifically instructed not to create a completely new security policy because the organisation already has one. In addition, the report should discuss how appropriate security measures could be implemented across the network. Detailed device configurations are not required, although relevant examples or configuration snippets are encouraged. Because the information provided in the case study is incomplete, students must identify and document their assumptions and requirements. This includes defining unspecified parameters such as network speeds, device features and existing policy details. The assumptions and requirements section is therefore an important part of the investigation and contributes to the assessment mark. The final report should summarise the key findings of the investigation and may recommend how any remaining IT support budget could be used. References must be included and used effectively to support the discussion. The marking criteria allocate 10% to the introduction, 10% to assumptions and requirements, 20% to improving performance, 20% to policy amendments, 20% to securing the network, 10% to the conclusion/summary and 10% to references. The assessed learning outcomes cover the application of network security concepts and protocols, critical evaluation and design of security policies, understanding of IT governance and its influence on organisational security policy, and critical review of current research and technological advances in network security. The brief also permits AI assistance, but any AI tools used must be referenced and their use summarised at the end of the report before the reference list.
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Digital Security Risk and Audit
2,000 words
Digital Security Risk and Audit – Information Security Audit of ABC Air
This individual coursework for the Digital Security Risk and Audit module requires students to prepare a 2,000-word information security audit report based on a case study involving ABC Air, a small aircraft service company responsible for aircraft maintenance for civil operators. The company records information including aircraft flying hours, servicing time, engineers' man-hours and related maintenance activities. An external contractor has also provided a report outlining a possible solution for ABC Air. Students are required to assess the information security risks associated with the scenario, complete an information security audit and produce a professional report, clearly identifying any assumptions made during the analysis. The assessment requires students to examine risk assessment, identification and analysis as part of the audit process. A suitable auditing approach must be selected and justified, with students considering either a general risk-based approach or a specific control-based approach. The report should explain why the selected approach is appropriate for the ABC Air scenario and demonstrate how it can be applied to the organisation's information security environment. The coursework also requires consideration of potential cyber attacks and their use within an integrated fault event analysis. Students must identify relevant information security threats and examine how an attack could affect the organisation and its information assets. The report should further identify appropriate standards, best practices or guidelines that could be used to mitigate information security breaches. These should be critically evaluated, including discussion of their advantages and disadvantages rather than simply being listed. The assessment develops students' ability to apply information security governance and audit practices within legal, ethical and professional contexts. It also requires consideration of recognised industry frameworks such as COBIT and international standards including the ISO 27000 series. Students are expected to perform systematic risk assessment and analysis, critically evaluate information assurance reference models, and select appropriate information security audit strategies for complex real-world scenarios. The marking criteria place particular emphasis on the quality of the information security audit, identification and adoption of appropriate international standards and frameworks, and critical evaluation of the benefits and limitations of security audit frameworks. The assessment allocates 20% to identifying and applying an appropriate audit approach, 50% to completing the conceptual information security audit and assurance, and 30% to interpreting and critically evaluating information assurance reference models. The report is an individual assessment and must be submitted as a PDF through Aula/Turnitin. The brief states that APA referencing should be used for the work and that all sources and any AI tools used must be acknowledged.
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Digital Data Acquisition, Recovery and Analysis
1,500 words
Digital Data Acquisition, Recovery and Analysis – Autonomous Vehicle Forensics
This individual coursework for the Digital Data Acquisition, Recovery and Analysis module requires students to produce a 1,500-word technical research paper critically investigating autonomous vehicle (AV) forensics. The assignment focuses on the challenges, methodologies and tools involved in extracting, preserving, analysing and interpreting digital evidence from autonomous vehicles and their associated systems. The work specifically considers how forensic evidence can be used to reconstruct events and establish accountability following accidents, security breaches or system malfunctions. The assignment examines the increasing importance of digital evidence generated by intelligent transportation systems and smart vehicles. Students are expected to consider data produced by different sources within an autonomous vehicle ecosystem, including LiDAR, radar and GPS sensors, vehicle control units and connected infrastructure. The report should explore how these different forms of information can be collected and forensically preserved while maintaining their evidential value for subsequent investigation and analysis. The coursework requires a detailed technical analysis rather than a general overview of autonomous vehicles or digital forensics. Students are expected to engage with academic literature, industry frameworks and technical examples, while providing critical insights into the subject. The report should analyse the practical challenges associated with AV forensics and critically examine the tools and methodologies that can be applied to obtain and interpret evidence from autonomous vehicle environments. Legal, ethical and privacy considerations form an important part of the assignment. The report should examine issues surrounding the use of autonomous vehicle evidence, including legal responsibility, regulatory considerations, privacy implications and ethical challenges associated with collecting and analysing potentially sensitive vehicle and user data. These considerations should be connected to the wider forensic investigation process and the reliability and admissibility of digital evidence. The required report should follow an academic research-paper structure, including a cover page, abstract, keywords, table of contents, clearly organised sections and subsections, references and an appendix where required. The brief requires APA referencing and a reference list at the end of the paper. Students are expected to use their own words and critically analyse the literature rather than simply summarising existing research. The assessment evaluates five equally weighted areas: structure and presentation with supporting references; balance, objectivity, critical evaluation and original insight; identification of AV-forensics challenges and quality of analysis; analysis of tools and methodologies used in AV forensics; and understanding of AV forensics together with its legal, professional and ethical considerations. Each area contributes 20% to the assessment.
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Network Security and Incident Report
1,500 words
Network Security and Incident Report – Megadodo Publications
This 1,500-word individual coursework for the Network Security and Incident Report module examines the network infrastructure and security challenges of Megadodo Publications, a company located near Warwick that has expanded into two buildings, Ursa Major Alpha and Ursa Minor Beta. Despite investment in new networking equipment, the organisation is experiencing poor network performance and repeated security incidents involving the leakage of sensitive information into the public domain. The situation is particularly urgent because the company is negotiating an important government contract. The student is placed in the role of a network security professional asked to investigate the existing environment and provide recommendations for improving its infrastructure and security. The case study provides a network topology, addressing scheme, equipment information and an existing security policy. The network connects departments across the two buildings and includes servers, management systems, sales, marketing, legal, finance, software development, product testing, administration, IT support, Wi-Fi and a rented floor occupied by a separate start-up company. The addressing scheme identifies separate subnets for several organisational functions, while the topology includes multiple switches, routers, servers and wireless access points. The report requires students to make reasonable assumptions where information is incomplete and document those assumptions at the beginning of the report. The first substantive task evaluates how the organisation's network performance could be improved. Recommendations should address the existing infrastructure and, where the design is changed, include an appropriate network diagram using tools such as Packet Tracer or other suitable applications. The second major area addresses amendments to the existing security policy. Students should recommend improvements to the current policy rather than create a completely new policy. The report must also discuss how appropriate security measures could be implemented across the network and its devices. Detailed device configurations are not required, although relevant examples or configuration snippets are encouraged. The final section requires a summary of the key findings and recommendations, together with a proposal for how the organisation could use its remaining IT support budget of approximately £8,000 and identify areas for future investment. The assessment is divided into introduction, assumptions and requirements, improving performance, policy amendments, security and devices, summary and budget, and references. The marking scheme allocates 50% of the module mark to this coursework, with the individual report submitted as a single DOC, DOCX or PDF document.
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1,500 words
Network Security Evaluation and Monitoring – Reconnaissance, Incident Response and APTs
This coursework assesses the research and analytical abilities required to design and evaluate an effective network security evaluation and monitoring solution. The scenario places the student in the role of a network security evaluation specialist responsible for helping a client design and build a monitoring solution for a complex client network. The client operates in the defence and security sector, works with government departments, multinational organisations and foreign agencies, and handles sensitive information. The network includes several server farms, gateway nodes, hundreds of client nodes, internal application services, externally accessible services and wireless access points. The organisation is considered vulnerable to threats such as sabotage and intellectual property theft. The coursework requires all questions to be answered in the given order within a single report. An abstract is not required, and students are expected to use technical terminology precisely. Relevant and clearly labelled illustrations are encouraged. Where assumptions are required about security software, hardware or services already deployed on the network, these assumptions must be clearly identified in a dedicated “Assumptions” section at the beginning of the report. Question 1 focuses on detecting network reconnaissance originating from inside the organisation. Students must explain how an insider could collect and use reconnaissance information for malicious purposes, identify the types of data that should be collected and the appropriate network locations for collection, and justify the selection of monitoring data. The question also requires recommendations for suitable tools and configurations to detect reconnaissance activity, together with strategies for dealing with the scale and high traffic volume of the client network. This section carries 30 marks and has a suggested length of 500 words. Question 2 focuses on incident response following a confirmed security incident. The scenario involves suspicious out-of-hours activity and an external flash drive connected to a workstation at gateway 10, a large number of files being opened on a file server at gateway 9, and significant traffic between the workstation and a database server at gateway 5. Students must determine which previously collected data would be relevant, explain the evidence expected from that data, and recommend additional network and endpoint data that should be collected. The proposed approach must be forensically sound so that evidence can potentially be used in court. This section carries 50 marks and has a suggested length of 700 words. Question 3 addresses Advanced Persistent Threats (APTs) and evaluates the effectiveness of the proposed monitoring solution. Students must recommend appropriate testing to determine whether the monitoring system operates according to its specifications and objectives, explain the types, timing and location of testing, and identify suitable qualifications, certifications, knowledge and tool experience for security testers. The section also requires discussion of APT behaviour and how the proposed monitoring mechanisms could detect or prevent such activity. This section carries 20 marks and has a suggested length of 300 words. Overall, the coursework develops skills in network security monitoring, reconnaissance detection, incident response, digital forensics, security testing and APT detection. It requires students to connect technical monitoring strategies with practical security, legal and operational considerations within a complex organisational network environment.
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Machine Learning and Big Data
2,000 words
Machine Learning for Big Data
This assignment for the Machine Learning and Big Data module requires students to produce a 2,000-word individual report demonstrating their understanding and practical application of machine learning techniques to big data. The assessment is worth 15 credits and is structured around five interconnected areas: data in big data, machine learning architecture, model deployment, model evaluation, and the machine learning lifecycle. The first part focuses on identifying and evaluating suitable datasets for a selected big data topic and determining whether the datasets are appropriate for the intended machine learning application. Students are expected to examine the characteristics of their data and apply appropriate pre-processing approaches, including consideration of attribute selection and data preparation. The second part addresses machine learning modelling architecture. Students must develop an appropriate architecture for their big data application and may compare alternative architectural approaches. The report should explain the selected machine learning techniques and demonstrate how they operate as part of the proposed system. Practical considerations such as performance, scalability, fault tolerance, technology usage and reliability should also be considered. The third part requires students to implement and deploy the proposed data and machine learning model. This includes testing, visualising and evaluating the resulting outcomes. The fourth part requires critical evaluation of the dataset selection, modelling design, implementation and application, including assessment of whether the selected machine learning techniques are appropriate for the intended purpose. The final part focuses on the complete project lifecycle. Students are expected to critically reflect on the work undertaken, identify what they have learned, evaluate the development process and explain how the machine learning application could be improved in a future implementation. The assessment develops five learning outcomes covering big data sources and applications, machine learning techniques, practical application of machine learning tools, critical evaluation of techniques and tools, and the ability to follow a complete big data analysis lifecycle. The marking criteria allocate 20% to each of these five areas. The assignment is submitted as an individual written report. The brief states that Microsoft Word should be used rather than PDF and requires students to acknowledge sources and any AI tools used in accordance with the stated AI policy.
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Programming for Data Science
4,000 words
Programming for Data Science – Individual Portfolio
This individual portfolio assessment for the Programming for Data Science module at Coventry University consists of four tasks designed to assess programming, debugging, data science, data visualisation, data protection and data ethics skills. The assessment carries 20 credits and has a total value of 4,000 words equivalent, excluding the reference list and output. Students are required to submit one clearly organised report containing all four tasks, with each task beginning on a new page. Python code, outputs and relevant plots must be included directly within the report. Task 1 focuses on analysing, critiquing and debugging Python code. Students are required to identify syntax errors, logical errors, style and readability issues in a supplied program, determine what the program is intended to calculate, and make appropriate corrections. Students must test the program using varying values, explain the changes made, and improve its overall readability and annotation so that an unfamiliar user can understand it. The task also requires students to investigate computational efficiency by measuring execution time for different input limits and identifying more efficient coding or logical approaches. Task 2 requires students to design, build and test a simple Python implementation of the Blackjack card game. The program should simulate a single-player game against a computer-controlled dealer, allow the player to choose between hitting and standing, automatically simulate the dealer's turn, and offer the option to play additional rounds. Complex rules such as splitting and betting are excluded, and students must not implement a Python class or graphical visualisation. The submission must include the Python code and the output from five games, with sufficient storytelling in the output to allow the code to be tested from the results shown. Task 3 assesses the student's ability to critically assess, select and apply data science tools. Students work with animal lifespan information from the AnAge database and use Python, including pandas and appropriate graphical libraries, to explore and communicate insights. The task involves summarising the number of animal species represented within each animal Class and producing plots of maximum longevity against adult weight for the four Classes with the most represented species. Students must discuss whether smaller or larger animals live longer, identify extreme outliers, compare trends between animal groups and consider implications for ageing research. Task 4 examines data protection and data ethics using the Cancer Genome Atlas (TCGA) as a case study. Students must explain how a potential data breach could occur, identify the personal and sensitive information that could be compromised, and discuss consequences for patient confidentiality, institutional reputation, participation in future research and possible legal or public relations responses. A second part considers a hypothetical UK database and requires discussion of GDPR and the UK Government Data Ethics Framework, including informed consent, anonymisation, transparency, ethical governance, privacy and public trust in biomedical research. The assessment assesses two module learning outcomes. MLO2 focuses on designing, building, testing, adapting and critiquing small programs in a high-level programming language and is assessed through Tasks 1 and 2. MLO3 focuses on critically assessing, selecting and applying data science tools, libraries or algorithms throughout the data science project lifecycle and is assessed through Tasks 3 and 4. The assignment requires APA referencing and asks students to provide in-text citations and reference lists where relevant. The brief also classifies the assessment as “Amber” for Generative AI: AI tools may be used for inspiration but not to generate answers or analyse datasets. Any permitted use must be clearly acknowledged, documented and cited using APA style.
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Ethical Hacking
2,500 words
Ethical Hacking – Professional Penetration Testing Report
This resit coursework for the Ethical Hacking module at Coventry University requires students to conduct a professional penetration testing examination of a small office environment represented by a number of virtual machines. The purpose of the assessment is to evaluate the security of the target environment, identify vulnerabilities, demonstrate appropriate exploitation techniques within the authorised assessment environment, and produce professional recommendations for improving the security of the systems. The assignment carries 15 credits and requires a report of approximately 2,000 words, with a permitted variation of ±10%. The report should follow a structured penetration-testing approach. The first section covers reconnaissance and target analysis, requiring students to investigate the target environment and identify its structure, services and potential attack surfaces. The marking criteria emphasise the use of appropriate tools to identify network structure and services and the identification of vulnerabilities during the scanning process. Students are expected to analyse the results rather than simply reproduce the output of scanning tools. The second section focuses on exploitation. Students must describe in detail the steps taken and the tools used to exploit relevant vulnerabilities identified during the assessment. The marking criteria distinguish between compromising the desktop and gaining access to the server, with higher achievement involving multiple relevant vulnerabilities and successful access through more than one vulnerability. The report should provide appropriate screenshots and sample sessions to support the findings. The third section addresses post-exploitation activities. Students are required to document and analyse activities carried out after gaining access to the target systems. Examples identified in the marking criteria include dumping password hashes and creating a persistent backdoor. For server assessment, the criteria also consider activities such as obtaining root access or establishing a persistent connection. The report should explain the significance of the activities rather than merely listing technical actions. The fourth section provides recommendations for securing the target machines. Recommendations must address all vulnerabilities identified during the assessment, not only vulnerabilities that were successfully exploited. Security issues should be discussed using an established risk-rating approach such as OWASP, and proposed countermeasures should be relevant to the specific vulnerabilities discovered. The report should also analyse how vulnerabilities relate to one another and fit within the wider security context. The final section presents the conclusions, including an evaluation of the penetration-testing work and alternative approaches that could have been taken. The overall learning outcomes require students to critically discuss the legal, technical and ethical scope of ethical hacking, evaluate penetration-testing methodologies and security assessment tools, analyse vulnerabilities, and professionally report penetration-test outcomes with suitable countermeasures.
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Cryptography
2,500 words
Cryptography – Secure Land Transaction Contract Exchange Protocol
This 2,500-word Cryptography coursework for Coventry University examines the design of a secure communication protocol for the remote exchange and signing of legal property transaction contracts. The assignment is based on a scenario involving Hackit & Run LLP (H&R), a firm of solicitors specialising in property transactions in the UK and overseas. Because property transactions are increasingly conducted through remote communications, H&R intends to establish a comprehensive system for secure document handling, exchange and digital signing that complies with legal requirements and remains enforceable under UK law. The scenario concerns a land transaction between Mrs. Harvey, the buyer, and Mr L.M. Facey, the seller. Students must devise a communication protocol involving three parties: H&R, the seller’s solicitor and Mrs. Harvey. H&R communicates with the seller through the seller’s solicitor rather than directly with the seller. The seller’s solicitor sends the contract to H&R, H&R forwards it to Mrs. Harvey, Mrs. Harvey digitally signs the contract and returns it to H&R, and H&R then sends the signed contract to the seller’s solicitor. The assignment requires students to consider two communication scenarios between H&R and the seller’s solicitor: a situation where the two parties have previously communicated securely and a situation where they are communicating securely for the first time. Students must identify suitable encryption algorithms for the different stages of the contract exchange protocol and justify their algorithm choices. The work should demonstrate an understanding of appropriate cryptographic approaches for maintaining confidentiality, integrity and availability during secure communication. Students must clearly illustrate their proposed protocol using suitable graphics and pseudocode. A full functioning implementation using a programming language may be provided as a higher-level approach. The report must identify the strengths and limitations of the proposed protocol and discuss the findings. This requires students to connect cryptographic theory with a practical security protocol designed for a real-world legal transaction. The coursework assesses knowledge of modern cryptography, including symmetric-key cryptography, key exchange, asymmetric cryptography, digital signatures, digital certificates and authentication. Students are also expected to model, test and assess the suitability of cryptographic protocols and algorithms for different practical requirements and critically evaluate current research and technological developments in cryptography and its applications. The final submission is a written report of 2,500 words, excluding appendices and tables, with properly formatted references. The assignment is categorised as a report and is a normal coursework attempt. The brief does not specify a particular referencing style or academic level, so these fields should not be guessed when entering the assignment into the Reference Library.
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Cryptography
2,500 words
Cryptography – Secure Contract Exchange Protocol
This 2,500-word Cryptography assignment for Coventry University examines the design of a secure communication protocol for the digital exchange and signing of property contracts. The scenario is based on Lauren Order & Cashgrab LLP (LO&C), a UK and overseas property law firm seeking to establish a comprehensive document handling, exchange and signing system that supports remote property transactions while remaining consistent with legal requirements and enforceable under UK law. The assignment requires students to consider the exchange of contracts using the extended CIA model and to devise a secure communication protocol involving three parties: LO&C, the buyer's solicitor Hackit & Run (H&R), and the seller. The scenario specifies that LO&C communicates with the buyer through H&R, that LO&C and the seller collaborate on initial contract drafts, and that LO&C prepares and sends the final contract to the seller for approval and digital signing before forwarding the signed contract to H&R for the buyer's signature. LO&C and H&R have an existing secure communication relationship. A central requirement is the identification and justification of suitable encryption algorithms for the different stages of the contract exchange protocol. Students may select algorithms covered in lectures or undertake additional research to identify alternative algorithms. The report must explain why particular algorithms are appropriate at different stages of the protocol and demonstrate how the selected cryptographic techniques address the practical security requirements of the scenario. The protocol must be clearly illustrated using suitable graphics and pseudocode, with functioning code being an optional higher-level approach. Students are required to identify the strengths and limitations of their proposed protocol and discuss their findings. The assignment therefore combines theoretical knowledge of modern cryptography with practical protocol design and evaluation. Generative AI may be used to create suitable code where permitted, but students must demonstrate their understanding of the code. The assessed learning outcomes cover modern cryptographic concepts and techniques, including symmetric-key cryptography, key exchange, asymmetric cryptography, digital signatures, digital certificates and authentication. Students are also expected to model, test and assess the suitability of cryptographic protocols and algorithms for practical requirements and critically evaluate current research and technological developments in cryptography and its applications.
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Software Development Project
Software Development Project – Group Presentation, Demo Video and Peer Assessment
This group-based assessment for the Software Development Project module at Coventry University requires a team of five students to design, develop and demonstrate a full-stack software product of their choice. The project must use technologies or platforms agreed by the team and requires students to contribute to different aspects of the software development process, including design, implementation and testing. The assessment is worth 20 credits and is submitted as a 15-minute MP4 presentation and demonstration video, with a permitted variation of plus or minus 10%. The main component is a group presentation and demo video. Students must evaluate the key Agile techniques applied during development and project management, supported by evidence of using appropriate software tools. The presentation should demonstrate how Agile practices were applied to the group project and should address techniques such as user stories with story-point estimation, story mapping, sprint planning, task boards, work breakdown and burndown charts. The assessment also requires evaluation of project risks and the social, professional, legal and ethical issues associated with the software project. A second major component is the live demonstration of the software features developed by the group. Students must demonstrate the most significant or innovative features implemented using their selected technologies and platforms. The demonstration should show how the software meets business requirements and provide a clear rationale for the development decisions. The marking criteria assess the quality, complexity and creativity of the software, including front-end, computation and back-end development, live data inputs and, where applicable, Create, Read, Update and Delete (CRUD) operations. The assessment also includes an individual peer-assessment component. Each student must rate every other team member's contribution using a whole-number score from 0 to 10, with 10 representing the highest contribution. The peer assessment accounts for 10% of the overall assessment, while the group presentation accounts for 60% and the software features demonstration accounts for 30%. The module learning outcomes focus on evaluating and applying appropriate software development approaches such as Agile, applying current technologies and platforms to meet business requirements, evaluating software solutions against quality metrics, and evaluating commercial risks alongside professional, social, legal and ethical considerations. The brief also places the assessment in the Amber AI category, meaning AI may be used to assist, but any AI tools used during the research process must be acknowledged and relevant AI-generated information must be cited and referenced using Coventry University APA style.
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Leadership and Change
3,000 words
Leadership and Change – Reflective Learning Portfolio
This 3,000-word coursework is a reflective learning portfolio focused on leadership, organisational change and reflective practice. The assessment is worth 100% of the module mark and is structured into four individual components. It is designed to assess leadership capabilities such as strategic thinking, emotional intelligence, communication, adaptability, team building, ethical decision-making and change management, while encouraging students to connect leadership theories and self-assessment tools with their own development. Component 1 focuses on individual leadership style and requires students to provide the results of the Fastest MBTI Test and critically reflect on what the outcome means in relation to their preferred leadership style. Students are expected to connect their MBTI results with leadership approaches covered in the module, including the Situated Leadership model. This component represents 20% of the assessment and has a suggested length of 600 words. Component 2 examines team roles. Students must present evidence from their Team Roles Test, identify their preferred team role and explain why it suits them. They must then identify two other Belbin team roles that would be important when building a team and explain their relevance. Connections can also be made between the Team Roles Test, Belbin’s framework and the results of the Conflict Management questionnaire. This component contributes 20% and has a suggested length of 600 words. Component 3 requires students to develop an individual organisational change plan in response to a fictional case study in which ARU is considering the adoption of AI to mark student coursework assignments and examinations. The plan evaluates change enablers and barriers, stakeholder involvement, ethical considerations and resource constraints. Students then develop an implementation strategy using a suitable change-management framework such as Lewin’s Change Model or Kotter’s 8-Step Model, including stakeholder engagement, communication, resistance management and strategies for sustaining change. This component represents 30% and has a suggested length of 900 words. Component 4 is a 900-word reflective account of what students learned about leadership while working as part of a team to design the organisational change plan. The reflection considers how leadership emerged, team collaboration, missing or required roles, conflict management and personal development. Students may structure the reflection using Kolb’s Reflective Learning Cycle or Gibbs’ Reflective Cycle and support their discussion with theories such as transformational, situational and distributed leadership, as well as Belbin’s team-role framework. Overall, the learning outcomes require students to critically reflect on their leadership style, evaluate classical and contemporary leadership theories, understand organisational change processes and develop evidence-based change strategies. The assessment also emphasises reflective practice and personal leadership development through experiential learning in a group setting.
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Network Systems and Administration
3,500 words
Network Systems and Administration – Linux System and Network Administration Portfolio
This assessment is an individual portfolio for the Network Systems and Administration unit. It consists of two quizzes and a report based on a case study involving the development, implementation, configuration, testing, maintenance, and evaluation of a network solution using an industry-standard network operating system. The report requires students to justify their design and implementation decisions, provide a detailed testing strategy, develop a maintenance and disaster recovery plan, and critically evaluate the completed solution. The case study concerns Piranha, a small organisation in which the business owner has been maintaining a server containing information relating to finance, management, production, and sales. The student is required to undertake the role of Network Systems Administrator and configure an appropriate Linux-based network environment. The practical work includes creating a new user account with root access, confirming root privileges, verifying access to company files, and configuring group-based access controls for finance, management, production, and sales directories. Students must then establish a client-server network by installing a Linux distribution on a separate virtual machine in VirtualBox. SSH connections are required to verify user access and the configured file permissions. The assessment also requires students to use Wireshark to observe network traffic during SSH sessions, report on packet types and encryption, identify potential security vulnerabilities, and recommend improvements such as SSH keys and unique passwords. A maintenance schedule and a brief disaster recovery or backup strategy must also be proposed. The final report must document the practical work with clear explanations and screenshots showing commands, user accounts, and results. The report should be between 1,500 and 3,500 words. The assessment also includes Linux Essentials and Networking Essentials final grades. The marking criteria cover system and network administration, the maintenance plan, reflection and report writing, screenshots, references, and Harvard referencing.
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Business Management / Strategy
2,467 words
Contemporary Issues in Business (BS729) — Reflective Portfolio: Case Trends, Stakeholder Perspectives and Management Frameworks
This Level 7 portfolio accumulates across a semester of case-based workshops and is submitted as a single document combining reflective writing with sustained critical discussion. The assessment rewards demonstrable personal development as much as analytical knowledge, so the writing is first-person where it needs to be and evidential throughout. The reflective component presents six workshop reflections, each no longer than 150 words and each structured through one of the established reflective models introduced in the module — Gibbs' Reflective Cycle, Kolb's Learning Cycle, Schön's framework or the ERA framework. These are not summaries of what the case was about. Each one identifies where the analysis could have been sharper, what was missed in the live discussion and why, what will be repeated and what will be done differently, with the emphasis falling on transferable learning about how business problems are diagnosed and decisions taken under uncertainty rather than on the particulars of any single case. The larger critical component works through three connected questions. The first examines how contemporary trends studied in the module affect businesses both positively and negatively, drawing on two specific cases but deliberately reaching beyond them to consider consequences across whole industries — the trend, not the company, is the unit of analysis. The second addresses why identifying stakeholders and understanding their perspectives is critical to sound decision-making, using one module case to demonstrate it. Competing interests are mapped explicitly, the power and legitimacy of each group considered, and stakeholder theory used to argue why a manager who weighs only shareholder interest arrives at a worse decision. The third question turns to the management tools and frameworks applied during the module, using two cases to show how a particular tool was selected, what it revealed that unstructured analysis would have missed, and equally where it fell short. This includes judgement about when each framework is and is not appropriate, since selecting the right tool for the problem is itself the skill being assessed. Harvard referencing is applied consistently across all sections, with academic sources supporting the theoretical claims and practitioner sources grounding the industry discussion. Portfolio items are collected through PebblePad across the semester and consolidated into one file for submission, the class participation element being tracked separately by the lecturer across the case discussion sessions.
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Digital Marketing / Marketing Analytics
2,483 words
Digital Marketing Analytics (BS783) — GA4 Performance Analysis and 90-Day Campaign Strategy for the Google Merchandise Store
This Level 7 report positions the writer as a digital marketing consultant engaged by the Google Merchandise Store, a live e-commerce operation. All quantitative work is drawn from the public GA4 Analytics Demo Account, so the analysis rests on real platform data rather than invented figures, and the report is structured in two halves that move from diagnosis to prescription. Part A is research and analysis. It opens by defining and evaluating the role analytics currently plays in shaping the store's digital marketing strategy — what is being measured, what that measurement is used for, and where the strategic gaps sit — grounded in marketing performance-measurement literature rather than description of the interface. The tactical analysis then assesses how effectively the store's digital channels and social content drove traffic and conversions across two defined quarterly reporting periods. Performance reporting follows, comparing the two periods in detail to identify the strongest customer segments, acquisition channels and products, and — more importantly — offering a reasoned explanation for why performance differed between them, distinguishing seasonality and campaign activity from genuine structural change. Part B turns to campaign strategy for a niche lifestyle market segment. A customer persona is developed and supported by the behavioural evidence visible in the GA4 data rather than asserted demographics, and a full journey map traces that persona from awareness through consideration, conversion and retention, identifying the friction points at each stage. Strategic recommendations then propose specific enhancements to channels and content aimed at that audience, each justified against the performance evidence from Part A and against the competitive landscape the store operates in. The final section builds the measurement architecture for the proposed campaign over the following ninety days. It sets goals and performance management parameters, selects the tools and metrics that will track them, defines the reporting cadence and the decision thresholds that trigger optimisation, and places particular weight on measuring return on marketing investment — connecting spend to sales, leads and customer satisfaction rather than to vanity engagement figures. Attribution limitations and the practical constraints of GA4 measurement are acknowledged where they affect confidence in the numbers. Throughout, screenshots and exported GA4 reports evidence the claims made, academic and practitioner sources support the analytical framing, and Harvard referencing is applied consistently. The submission is a single file through Turnitin.
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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 real-world customer-service analytics scenario. Acting as a Data Scientist, students analyse a historical Customer Service Escalation Risk dataset to help an organisation reduce serious and legal customer escalations by identifying early signs of dissatisfaction, service bottlenecks and operational risk. The findings are intended to support business decisions relating to staffing, employee training, customer-journey improvement and escalation prevention. The dataset contains information covering customer demographics, account characteristics, communication channels, issue categories, operational measures such as wait 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 contains four escalation outcomes: No escalation, Minor escalation, Serious escalation and Legal escalation. The first stage requires data exploration, visualisation and summary, including examination of variable distributions, dataset structure, descriptive characteristics and potential data-quality issues. Students then perform appropriate data cleaning, transformation, feature engineering and preprocessing. Particular attention must be given to variables that could introduce prediction leakage because of their meaning, timing or reliability. The supervised-learning component requires development and tuning of predictive models using suitable techniques such as k-nearest neighbours, Decision Trees, Support Vector Machines, ensembles or neural networks. Models must be evaluated using appropriate multiclass metrics and compared systematically, with interpretation of influential features and model behaviour. The assessment also requires unsupervised learning. After removing the escalation target, students apply and compare clustering approaches such as K-Means and hierarchical clustering. Appropriate preprocessing, encoding, normalisation or dimensionality reduction may be used, with visualisations such as PCA, t-SNE or scatterplots used to explore cluster structure and its relationship with escalation behaviour. Overall, the project assesses the student's ability to independently design a coherent KDD workflow, justify analytical decisions, compare alternative modelling approaches and communicate actionable findings to both technical and executive audiences. Overview word count: approximately 350 words. AI-use note: the brief permits AI tools only to assist with small, specific code snippets. Any AI-generated code must be clearly acknowledged and cited, while the submitted coding, analysis, interpretation and decision-making must remain the student's own work.
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Cyber Security / Cloud Management
2,500 words
Cyber Security and Cloud Defence Strategy for ShieldSafe Analytics
This Level 7 Cyber Security for Business and Cloud Management portfolio examines the security challenges faced by ShieldSafe Analytics Ltd., a multinational health analytics organisation specialising in AI-enabled diagnostics and telehealth. The organisation processes high volumes of sensitive patient information, including biometric and genomic data, across hybrid-cloud environments and IoT-enabled healthcare infrastructure. Following a suspected data-exfiltration incident involving anomalous traffic from a diagnostic platform connected to third-party cloud APIs, students are required to evaluate the organisation's information environment and develop appropriate cyber-security and cloud-defence strategies. The first task focuses on information environments and the weaponisation of information. Students identify critical elements of ShieldSafe's information environment, evaluate vulnerabilities associated with the data-exfiltration incident and examine how patient data or analytical systems could be manipulated by malicious actors. Relevant real-world healthcare cyber incidents should be used to support the analysis. The second task examines offensive and defensive Information Operations. Students analyse techniques used by nation-state actors and cybercriminal organisations, including healthcare ransomware incidents such as WannaCry, and compare offensive and defensive approaches. The analysis considers how ShieldSafe can balance these approaches while protecting sensitive data and preserving trust in AI-enabled diagnostic systems. The third task applies Information Operations within legal and ethical boundaries and requires development of a secure cloud migration strategy for ShieldSafe's legacy Electronic Health Record system. The supporting student guide specifically permits students to demonstrate an implementation using Amazon AWS, including IAM users and roles, VPC configuration, security groups, web servers, EC2 instances and AWS migration services. The final task requires a comprehensive cyber-defence strategy, including implementation of Zero Trust Architecture across cloud platforms and analysis of vulnerabilities affecting cyber-physical healthcare systems such as wearable medical devices and diagnostic equipment. Students must propose controls against both remote and local attacks. Overall, the portfolio integrates information operations, healthcare cybersecurity, hybrid-cloud protection, secure migration, Zero Trust, cyber-physical security and strategic cyber defence. The work is produced as a portfolio report using PebblePad and must use Harvard referencing throughout, with appropriate citation of academic sources, images, definitions and external arguments.
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Machine Learning and Deep Learning
2,000 words
Development and Evaluation of Deep Learning Models for Healthcare Classification
This individual technical assessment focuses on the design, development, analysis and evaluation of a deep learning solution for a healthcare-related classification problem. Students select one of two provided scenarios: Polycystic Ovary Syndrome (PCOS) detection using ultrasound images or heartbeat classification using electrocardiogram (ECG) signals. The objective is to develop an appropriate deep learning approach and demonstrate critical understanding of the complete machine learning workflow, from initial data exploration through to model evaluation and reflection. Students may either design and train a deep learning model from scratch or customise and fine-tune an existing pre-trained architecture. The complete work is presented through a single Jupyter Notebook integrating Python code, technical discussion, results and visualisations. The notebook must clearly define the selected healthcare problem, explain its significance, justify methodological and architectural choices, and critically evaluate the resulting solution. The first stage involves exploratory data analysis and preprocessing, including investigation of class distributions, data imbalance and relevant patterns. Students prepare the data through techniques such as normalisation, augmentation, train-validation-test splitting and appropriate handling of class imbalance. This is followed by model design, training, validation and hyperparameter tuning, with the architecture selected according to the characteristics of the data and classification task. Model performance must then be evaluated using appropriate classification measures, including precision, recall, F1-score, ROC curves and area under the curve (AUC). The developed model should also be compared against suitable benchmark approaches, which may include traditional machine learning algorithms or alternative deep learning architectures. This comparison should identify the relative strengths and limitations of the proposed solution. The final component requires clear visual presentation and critical reflection on the complete modelling process, including limitations, challenges and opportunities for improvement. Importantly, grading prioritises methodological rigour, analytical depth and critical evaluation rather than simply achieving the highest predictive accuracy. Overview word count: approximately 330 words. AI restriction: this brief only permits automated AI tools for spelling and grammar checking. It explicitly prohibits tools such as ChatGPT, Gemini or Copilot from authoring assessment text or code; any permitted AI use must also be acknowledged.
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Business Intelligence / Data Analytics / Project Management
Business Intelligence and Data Analytics for Project Progress Evaluation
This assessment for the Data Analytics and Project Management for Business Intelligence module requires students to critically evaluate the progress of a live-style project through the application of business intelligence and data analytics techniques. Working as a group of Project Analysts, students select either a Convocation project or Concert project associated with Northumbria University London and prepare a professional presentation assessing its progress, stakeholders, deliverables and performance. The assessment begins with development of a clear project problem or opportunity statement, followed by identification and analysis of the key stakeholders and deliverables associated with the selected project. Students then use Business Intelligence and Data Analytics techniques to examine project progress and communicate findings through dashboards. The assessment permits the use of Microsoft Excel or other suitable software for dashboard development. A central part of the task is the creation and critical evaluation of a project dashboard. Students are expected to use realistic assumed or projected data where necessary, as the assessment is designed to test the ability to design, interpret and critically evaluate dashboards rather than the accuracy of real project data. The data should therefore be internally consistent, relevant to the selected project and capable of generating meaningful management insights. Students must also critically justify their chosen BI and analytics tools, explaining how the dashboard supports project monitoring and informed decision-making. The assessment concludes with recommendations for the successful implementation and use of a Business Intelligence or Data Analytics solution within the selected project. Academic references and relevant examples should be used to support the analysis. The marking criteria place the greatest emphasis on application of BI tools and techniques (30%), followed by stakeholders and deliverables (20%) and justification of BI tools (20%). Project and opportunity analysis, conclusion and recommendations, and presentation and referencing each contribute a further 10%. Higher-performing work is expected to demonstrate critical evaluation, meaningful dashboard insights, strong theoretical or industry justification and professionally presented recommendations. If the file you want to upload is the resubmission report instead Use the same University, Subject and Module Name, but change these fields: Title: Business Intelligence and Project Analytics: Individual Critical Analysis of Project Performance Assignment type: MS Technical and Scientific Writing Word count: 1,500–2,000 words Key topics: Business Intelligence, Data Analytics, Project Management, Stakeholder Analysis, BI Tools, Dashboard Evaluation, Project Opportunity Analysis, Project Deliverables, Critical Analysis, Project Recommendations The resubmission is an individual written report in which the student selects only one area from the original project—Project & Opportunity Analysis, Stakeholders & Deliverables, Application of BI Tools & Techniques, Justification of BI Tools, or Conclusion & Recommendations—and develops it in depth. It should use the same Convocation or Concert project context while demonstrating independent critical analysis, reflection and application of theory.
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Cyber Security / Penetration Testing
2,400 words
Grey-Box Penetration Testing: Vulnerability Assessment, Exploitation and Mitigation
This technical cyber-security project presents an authorised grey-box penetration test conducted within a controlled virtual laboratory environment. The objective is to assess the security posture of a deliberately vulnerable target system, identify weaknesses in exposed network services, demonstrate how those weaknesses could be exploited, evaluate their security and organisational impact, and recommend appropriate mitigation measures. The assessment follows a practical penetration-testing workflow supported by technical evidence, screenshots, activity records and academic research. The project begins with laboratory configuration, network discovery, service enumeration and vulnerability analysis. Tools including Kali Linux, Metasploitable, VMware, Nmap, Netcat and Metasploit are used across the testing lifecycle. Identified services are mapped to known vulnerabilities before controlled exploitation is undertaken and the resulting access is documented. The activity log records the progression from environment setup and network scanning through vulnerability identification, exploitation, evidence collection and final reporting. Five principal attack vectors are examined. These include the vsftpd 2.3.4 FTP backdoor, Samba username-map-script exploitation, an UnrealIRCd backdoor, insecure Java Remote Method Invocation and a misconfigured DistCC service. The practical demonstrations show how vulnerable or incorrectly configured services can permit unauthorised command execution and, in several cases, privileged shell access. For each vulnerability, the report explains the weakness, exploitation process, observed result, security impact and proposed mitigation. Recommended controls include patching or upgrading obsolete services, disabling unnecessary services, implementing firewall restrictions, strengthening authentication and input validation, restricting access to authorised systems, applying least privilege and monitoring suspicious activity. The project also incorporates group management and reflective practice. Team members perform specialised roles covering laboratory configuration, reconnaissance, vulnerability analysis, exploitation and documentation. Individual reflection considers technical performance, teamwork, evidence management and future skills development, demonstrating how structured collaboration contributes to an effective penetration-testing engagement. Important: unlike the earlier assignment briefs, these uploads appear to be completed student/project materials rather than the official 7COM1068 assessment brief. Therefore I would not invent the university, academic level or academic year. If you upload the actual 7COM1068 assignment guideline, I can fill those fields exactly.
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Machine Learning / Data Science
Linear Regression and Stability of the Moore–Penrose Pseudoinverse Using Python
This machine learning practical and assessment activity develops an understanding of linear regression, Ordinary Least Squares and the Moore–Penrose pseudoinverse using Python. The work progresses from generating synthetic regression datasets to implementing regression algorithms manually, applying established machine learning libraries, analysing real datasets and evaluating the stability of estimated regression coefficients. The laboratory component begins with the generation of synthetic linear regression data using NumPy, including explanatory variables, random noise and an outcome variable. Students then implement simple linear regression without relying on machine learning libraries, using the least-squares solution to estimate the intercept and slope. The resulting observations and fitted regression line are visualised using Matplotlib. The work is subsequently extended to multiple linear regression, where several independent variables are used and coefficients are first calculated manually before the same problem is solved using Scikit-learn. The laboratory also introduces application of regression to the Scikit-learn Diabetes dataset, including feature and target standardisation, model fitting, prediction, correlation analysis and interpretation of regression coefficients. It also highlights the importance of residual analysis when assessing whether a linear model is appropriate. The associated weekly challenge focuses on the stability of linear regression solutions estimated using the Moore–Penrose pseudoinverse. Using a house-price dataset containing variables such as property size, number of bedrooms, distance from the city centre and property age, students construct the design matrix, standardise features and the response variable, and calculate regression coefficients using the pseudoinverse. Students then investigate model robustness by repeatedly fitting the regression model to random subsamples of different sizes and analysing the mean and standard deviation of each coefficient. Tables, boxplots or error-bar visualisations can be used to compare coefficient variability. The final discussion considers which variables are most influential, which coefficients are most stable, how sample size affects stability and whether coefficient interpretation remains reliable across different samples. The final work is submitted as a single PDF exported from Jupyter Notebook or Google Colab, combining documented Python code, experimental results, plots and written interpretation in a professionally organised notebook. Overview word count: approximately 360 wor
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Cloud Computing / Big Data Technologies / Cyber Security
2,500 words
Cloud and Big Data Security Application: Design, Implementation and Evaluation
This assessment for the Cloud and Big Data Technologies module requires students to design, implement and evaluate an individual cloud-based or distributed data application. The project focuses on practical solutions involving the complex transformation, processing, storage and security of big data within cloud environments. Students are expected to demonstrate how distributed data can be organised in the cloud, how data pipelines can be used to access or process distributed databases, and how appropriate security controls can be incorporated into the resulting architecture. Students have considerable freedom when selecting their application. Suggested project directions include developing a data-science solution using SQL or MongoDB with cloud storage and an appropriate security policy; implementing privacy-preserving distributed processing using techniques such as Differential Privacy; creating multi-party authentication and group-based access-control mechanisms; or designing Multi-Level Security, Attribute-Based Encryption or Role-Based Access Control solutions. Projects may also examine distributed or cloud applications using security protocols such as SSH, SSL or IPsec. Creativity and originality are explicitly encouraged. The written component is a Design and Implementation Document of no more than approximately 2,500 words. It should present the project aims and objectives, application concept, cloud and security technologies, functional and security requirements, architecture and design decisions, protocols, access-control mechanisms, implementation process, achievements, problems encountered and overall evaluation. Relevant diagrams, such as interaction or sequence diagrams, may be used to explain system behaviour and architecture. The assessment also requires submission of the functioning Cloud and Big Data Security application and a 7-minute highlight demonstration video. The video should demonstrate the application's major features, implementation details, security functionality and, where appropriate, attack scenarios. Assessment places strong emphasis on the quality of the design and implementation documentation, originality, use of advanced features, and the overall effort and technical quality of the completed application. Students are therefore expected to demonstrate independent development rather than simply reproduce an existing tutorial.
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Cyber Security / Digital Forensics
3,500 words
Digital Forensics Portfolio: Disk Image, Memory and Windows Registry Investigation
This Level 7 Digital Forensics portfolio requires students to conduct a structured forensic investigation across disk, memory and Windows Registry evidence. The assessment develops practical investigative skills alongside professional forensic reporting and requires students to preserve evidence integrity, document methodology, interpret technical artefacts and communicate findings clearly. The portfolio is equivalent to 3,500 words and forms 60% of the module assessment. The first part involves analysing a seized USB forensic image in the context of a suspected insider involved in video piracy and potentially more serious criminal activity. Students must follow ACPO digital forensic best practice, verify image integrity before and after examination, maintain a clear chain of custody, identify significant device properties and artefacts, and justify conclusions using evidence. Tools such as FTK Imager and Autopsy may be used, alongside other appropriate forensic utilities. The scenario also requires examination of an encrypted VeraCrypt container discovered within the evidence. The second part focuses on memory forensics using a Windows memory dump. Students are expected to reconstruct process execution timelines, examine suspicious processes including PowerShell, Notepad and AtomicService, identify process owners and SIDs, extract relevant memory artefacts and produce an executive summary suitable for a non-technical audience. The third part requires an extensive Windows Registry and system artefact investigation. Students examine operating-system information, users, network configuration, login activity, suspicious files, executable and DLL creation, BAM records, Prefetch artefacts, scheduled tasks, persistence mechanisms and evidence of potentially malicious activity. Findings must be supported with screenshots, extracted artefacts or other appropriate evidence. The assignment must use the university's official portfolio template and be submitted as a PDF. The template organises the work into forensic image analysis, memory investigation and Windows Registry investigation sections. For a public Reference Library entry, this title is better than simply “Digital Forensics Coursework” because it clearly communicates the three major technical components of the work.
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Business Intelligence / Data Analytics / Project Management
Business Intelligence and Data Analytics Dashboard for Project Progress Evaluation
This group assessment requires students to act as Project Analysts and critically evaluate the progress of a university project using business intelligence, data analytics and project management techniques. The scenario is based on Northumbria University London planning two major events: a Convocation and an associated Concert. Students must select one of these projects and assess its progress through a professionally structured presentation. The assessment requires students to begin by defining the main problem or opportunity associated with the selected project. They must then identify and analyse the project's key stakeholders and deliverables. A major component of the work involves evaluating project progress using suitable business intelligence and data analytics techniques and developing an appropriate dashboard, which may be created using Microsoft Excel or other suitable software. Students must not only present the dashboard but also critically analyse and justify its design, selected metrics, analytical methods and usefulness for project monitoring and decision-making. Because the projects are treated as already being in progress, students are permitted to create assumed or projected data to demonstrate their dashboards. The assessment does not primarily evaluate the accuracy of real project data; instead, it assesses students' ability to design, present and critically evaluate meaningful dashboards. Any assumed data should therefore remain realistic, internally consistent and relevant to the selected project. The presentation should conclude with evidence-based recommendations for the successful implementation and use of the proposed business intelligence or data analytics solution. Academic references and relevant examples must support the presentation, and a single reference list must be included. Assessment weighting places particular emphasis on application of BI tools and techniques (30%), followed by stakeholders and deliverables (20%) and justification of BI tools (20%). Project and opportunity analysis, conclusions and recommendations, and presentation/referencing are each worth 10%. The final assessment is a 15-minute group presentation followed by a 5-minute question-and-answer session. Every group member must contribute to the presentation. The PowerPoint submission is made electronically through Turnitin. Do not select Harvard automatically for this one. Unlike the previous Roehampton brief, this Northumbria brief requires academic references and a reference list but does not state a specific referencing style in the uploaded document.
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Global Supply Chain Management / Operations Management
2,494 words
Global Supply Chain and Operations Performance: Company Case Analysis
This Level 7 individual assignment requires students to produce a 2,500-word company case analysis examining an important operations performance issue within a real organisation. Students may select an organisation of any size, type, industry or country and must concentrate their analysis on one operations performance objective: cost, dependability, flexibility, speed or quality. The report requires students to identify the current challenges faced by the chosen organisation in relation to the selected performance objective and critically examine those challenges using relevant operations and supply chain management theories, concepts and analytical tools. Rather than providing only a descriptive account of organisational activities, students are expected to apply appropriate theoretical frameworks to the case and evaluate how these concepts could contribute to improved organisational and supply chain performance. A significant component of the assignment involves critically discussing appropriate best practices for performance improvement. These may include digital technologies, sustainability practices or other relevant operational and supply chain approaches. Students should connect these practices directly to findings from their chosen company case and assess their practical relevance, opportunities and limitations. Academic literature and appropriate real-world evidence should be used throughout to substantiate the analysis and recommendations. The assignment evaluates students' ability to analyse supply chain and operations problems, apply academic theory to organisational practice, and develop evidence-based conclusions and practical recommendations. The marking rubric places substantial emphasis on analysis and discussion (30%), application of theory (30%), and conclusions and recommendations (30%), with the remaining 10% allocated to presentation, logical structure, English expression and correct referencing. The report must use Harvard referencing, include a contents page, and follow the specified academic formatting requirements, including Arial size 12, 1.5 line spacing and A4 pages with 2.54 cm margins.
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Digital Marketing and Analytics
2,974 words
Digital Marketing Analytics Consultancy Report — Accessibility, Social Listening and Web Analytics for an E-Commerce Storefron
This assessment places the student in a consultancy role advising a global brand's e-commerce storefront on its digital marketing strategy. It is written as a business report rather than an academic essay, in the third person, with appendices used only for supporting material that the main text explicitly refers the reader to. The work is built from four analytical layers, and the mark weighting tells students where the effort belongs. The first is an accessibility and user experience evaluation of the client site benchmarked against two self-selected industry competitors — the selection itself must be justified, and the analysis must cover both technical and content dimensions using recognised evaluation tools rather than impressionistic browsing. The second layer, carrying the smallest weight, is social listening: which networks the brand and its competitors are active on, what engagement looks like, which content types perform, and who the influential voices are. This is paired with qualitative sentiment or content analysis of actual social comments, on the premise that quantitative engagement metrics describe reach but not attitude. The third and heaviest layer is quantitative analysis using a web analytics platform, typically via a demonstration account that provides real traffic data. Students query the data themselves and extract performance insights. Comparison across time periods is what separates competent work from strong work here: a single-period snapshot describes, while period-over-period comparison explains. The fourth layer, weighted equally with the analytics, asks the student to synthesise everything into strategic recommendations for the coming year, covering areas such as customer segments, user behaviour, landing and exit page performance, search ranking positions, advertising budget allocation, marketing channels and e-commerce performance. This section is where most marks are lost. Recommendations that do not trace back to a specific finding from the preceding analysis read as generic digital marketing advice, and rubrics at this level penalise exactly that. Presentation requirements are prescriptive — specified font, size, line spacing and justified margins — and the report is expected to be concise despite the breadth of analysis, which makes ruthless selection of evidence part of the task. A draft submission point for similarity checking is usually provided separately from the marked final submission. Assessments of this type commonly require a signed declaration itemising any AI tool use, with an explicit confirmation that AI was not used to generate sentences, paragraphs or sections. Our support on assessments of this type is guidance-based. Typical areas of help include: explaining how accessibility evaluation tools are used and what their output actually shows, clarifying the difference between reporting analytics figures and interpreting them, showing how a recommendation should be traced to a specific finding, advising on report structure and appendix discipline, checking APA consistency, and reviewing a student's own draft against the published rubric.
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Marketing
4,000 words
Strategic Recovery Marketing Report — Diagnosing Underperformance and Building a Sustainable Turnaround Plan
This is a case-based marketing assessment in which the student selects a real business that is currently underperforming or failing, diagnoses the causes, and builds a full marketing recovery strategy for it. The company choice is the student's own but requires module team approval, so the selection itself carries risk: a firm with thin public disclosure will starve the analysis, while an over-documented household name invites description rather than diagnosis. The deliverable is a formal report of around four thousand words, excluding references and appendices, referenced in APA 7. Appendices can carry supporting data, models and supplementary analysis, but not core content — a common way marks are lost is pushing substantive argument into an appendix to stay within the word limit. The report has two linked halves that students often treat as separate. The first is diagnostic: why is this business underperforming? This demands explicit application of marketing theory rather than a narrative of the company's troubles assembled from press coverage. The second is prescriptive: a recovery strategy that follows from the diagnosis. Recommendations that could have been written without the analysis — refresh the brand, invest in digital, improve customer experience — score poorly regardless of how well they are expressed. Where this module differs from a generic strategic marketing assessment is the sustainability and ethics dimension. The learning outcomes centre on sustainable marketing, social responsibility, and the intersection of marketing technology with sustainable practice. The marking criteria reward conclusions that show awareness of ethical and sustainability dimensions at every band above a pass. A recovery plan built purely on cost and revenue logic will therefore underperform against the rubric even if it is commercially sensible. The strongest submissions treat sustainability as part of the recovery mechanism rather than a section appended at the end. Assessments of this type increasingly sit within a tiered AI policy. Where a permissive tier applies, students may use AI tools for idea generation, structuring, source discovery, summarising notes, and proofreading or feedback — but not for producing the analysis itself — and must declare which tools were used and how, usually in a table placed before the reference list. Students are also expected to retain evidence of how their thinking developed, such as version histories or drafts, which can be requested if misconduct is suspected. Our support on assessments of this type is guidance-based. Typical areas of help include: advising on company selection and data availability, explaining how a diagnostic framework should structure an argument, showing the difference between descriptive and evaluative use of theory, clarifying how sustainability criteria are actually assessed in a marking rubric, checking APA 7 consistency, and reviewing a completed draft against the published criteria.
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Entrepreneurship and Business Start-up
5,000 words
Enterprise Start-up Portfolio — Business Plan, Fundraising Strategy and Entrepreneurial Self-Assessment
An enterprise start-up portfolio assessment asks students to originate a business idea and build the full supporting case for it, then present that case both in writing and as a recorded investor pitch. It is a pass/fail module structure in which every component must be passed individually — a strong business plan cannot compensate for a weak pitch, or vice versa. The written portfolio divides into two unequal halves. The larger part is the business plan itself, built to a fixed section structure with prescribed word allocations: an executive summary; the business idea set against an identified market gap, with market research and competitor analysis; customer profiles and segmentation; product development; marketing and communications; financials and business models covering costing, pricing, sales and revenue; and the founding team with its core competencies. The word allocations are not decorative — financials carry the single largest weighting in both the word budget and the marking rubric, which tells students where analytical depth is expected and where concision is. The smaller part is reflective. It covers the fundraising strategy — which funding sources are realistic for this venture, and how each would be targeted, approached and secured — and the student's own entrepreneurial tendency, informed by a standardised self-assessment instrument taken online. The rubric here rewards critical self-reflection over description: reporting a test result scores poorly; interpreting what the result means for how this founder should build a team and where they need support scores well. The pitch component is assessed on visual and audio quality, content and message, comprehension, delivery, and evident preparation. Technical execution carries real marks, which students routinely underestimate. Two things separate strong submissions. The first is internal consistency: the revenue model must follow from the pricing, the pricing from the customer segment, the segment from the identified gap. Plans that read as seven separate essays under seven headings lose marks even when each section is individually competent. The second is specificity in the financials — costing assumptions stated and justified, rather than round numbers presented without derivation. Note that assessments of this type commonly require the student to retain all drafts and earlier versions of their work, and to sign a detailed declaration itemising exactly how any AI tools were used. Our support on assessments of this type is guidance-based. Typical areas of help include: explaining what a market gap argument needs to be credible, showing how competitor analysis should be structured rather than listed, clarifying how costing and pricing assumptions should be built and presented, reviewing whether a fundraising strategy matches the venture's actual stage, explaining how reflective writing is assessed at postgraduate level, and checking a completed draft against the published rubric.
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mgt
This module requires you to complete two assessments: a group presentation (25%) and an individual report (75%). In the group presentation, your team must analyse a chosen industry using strategic tools such as PESTEL analysis, Porter’s Five Forces, and competitor/strategic group analysis. The presentation should critically evaluate the external and industry environment, include graphs, charts, and academic references, and demonstrate strong teamwork and confident delivery during the 15-minute presentation and 5-minute Q&A session. The individual report requires you to select a company from the recommended list and critically evaluate its strategic challenges, business ethics, sustainability practices, and/or organisational culture issues. You must analyse the impact of these issues on the company, provide well-justified recommendations, suggest suitable leadership and management approaches, and support all arguments using relevant strategic and leadership theories. The work should be analytical rather than descriptive, properly referenced with in-text citations, professionally formatted, and based on extensive research.
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