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Academic and Employability Skills and Research Methods and Masters Dissertation
1,800 words
Personal Development Plan: Academic, Employability and Career Development
This assessment requires students to develop a Personal Development Plan (PDP) related to their chosen field of work and future career pathway. The assignment is designed to support the development of academic, employability, professional and research-related skills while encouraging students to critically reflect on their current capabilities and identify areas for further development. The assessment consists of three interconnected components presented together as one document. The first component is a 750-word academic report that critically evaluates employment and entrepreneurial opportunities within the student's chosen field of work. Students are expected to use a range of relevant academic and professional sources to investigate the knowledge and skills required for their chosen career area, available employment opportunities, entrepreneurial opportunities and the challenges associated with the field. The chosen field must be clearly related to the student's study pathway specialism. The report should be presented in an appropriate academic structure, including an introduction and conclusion. The second component is a 750-word self-analysis and action plan. Students are required to critically reflect on their own strengths and weaknesses in relation to their chosen field of work or career path. The reflection should be supported by relevant academic and professional literature and should demonstrate awareness of personal qualities, employability requirements and areas requiring further development. Students must identify three specific action points for personal development that will enhance their readiness for their career goals. The third component is a portfolio of completed tasks, included as appendices to the assessment. These tasks provide evidence of the student's development and include activities relating to the chosen field of work, report planning, self-analysis and a SMART action plan. Evidence of completed tasks and Turnitin submission receipts is also required. The assessment encourages students to develop awareness of their personal strengths and weaknesses, engage in continuing self-development and build the skills required for employment and career progression. It also relates to research, employability and entrepreneurship competencies, including knowledge of hard and soft skills, systematic planning, critical analysis, professional development, ethical awareness, self-direction and independence. The complete assessment has a 1,500-word limit with a permitted variation of plus or minus 10%. Part 1 and Part 2 each contribute 40%, while the portfolio tasks contribute 10% and professional presentation contributes 10%. The assignment should be submitted as one professionally presented document and follow APA style guidelines.
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Global Supply Chain Management
1,800 words
Suez Canal Blockage: A Case Study of Global Supply Chain Disruption
This individual report examines the challenges faced by global supply chains as a result of the Suez Canal blockage and critically evaluates the factors that affected supply chain performance during the disruption. The assignment uses the Suez Canal blockage as a case study to explore the wider principles and practices of global supply chain management, with particular attention to supply chain disruption, risk management, resilience, logistics, supplier relationships and integrated supply chain performance. The report requires students to conduct preliminary research into the Suez Canal blockage and use relevant academic and practical sources to identify the major challenges created by the disruption. The case study focuses on the six-day stranding of the Ever Given and the resulting disruption to international supply chains and global trade. The assessment considers how a disruption at a strategically important global trade route can create wider consequences for organisations, logistics networks and supply chain operations. The analysis should identify the key factors that influenced supply chain performance and critically evaluate the effectiveness of the solutions implemented to resolve the disruption. Relevant global supply chain management theories, models and concepts should be clearly defined and applied to the case rather than simply described. The report should demonstrate an understanding of fundamental supply chain principles and consider how evolving trends and global issues can affect supply chain operations. The assignment also encourages consideration of important supply chain management areas covered within the unit, including risk management, resilience, outsourcing, supplier planning and selection, relationship management, supply chain integration, demand management, order management and customer service. These concepts should be connected to the Suez Canal blockage to provide a critical assessment of the challenges and possible approaches to improving supply chain resilience. The report must be presented in a formal and logically coherent report format and should provide evidence of critical reasoning through a wide range of relevant academic and practical sources. The conclusion should draw together the main findings, while recommendations should propose realistic approaches for addressing the supply chain issues identified in the case. The assessment is worth 30% of the overall unit mark and requires an individual report of 1,800 words, with a permitted variation of ±10%. The report is assessed across four main areas: use of theory and frameworks (25%), analysis and evaluation (30%), conclusions and recommendations (20%), and structure, presentation and referencing (25%). The marking criteria emphasise the application of relevant theoretical concepts, critical evaluation of academic and practical sources, a clear connection between theory and practice, realistic recommendations, logical structure, and appropriate in-text citations and referencing.
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International Business Strategy
250 words
Individual Reflection on Case Study Discussion – International Business Strategy
This assignment is an individual reflective assessment for the International Business Strategy module. It focuses on developing students’ ability to critically reflect on their learning experiences and identify how learning from classroom discussions can improve their future academic and professional performance. The assessment is based on a Case Study Discussion undertaken during one of the teaching weeks from Week 5 to Week 8. Students are required to select one of the case studies discussed during the relevant seminar sessions and reflect on their learning from the discussion. The case-study discussions provide an opportunity to explore important issues in the business world, apply concepts introduced through Canvas preparation and face-to-face teaching, and exchange ideas with tutors and peers. The reflection therefore connects theoretical knowledge with practical business situations and encourages students to consider how strategic management concepts can be applied to real-world organisations. The reflective task requires students to explain the topic and case study discussed during their selected week, identify what they learned from the discussion, and consider how the experience helped them develop their ability to apply theories to their chosen company. Students should also reflect on their key takeaways, what went well during the discussion, challenges they encountered, and what they would change if they were to repeat the experience. The reflection should be between 150 and 250 words and should use an appropriate reflective framework, such as Gibbs' Reflective Cycle or Kolb’s Experiential Learning Cycle, to structure the discussion. Harvard referencing should be used where applicable. The assessment develops critical reflection, strategic thinking, international business understanding and the ability to connect academic concepts with practical business cases. The assessment is worth 15% of the module and is submitted through Canvas. The marking criteria consider the quality of reflection, critical analysis, personal learning insights, presentation and structure, intellectual curiosity, referencing, content and discussion.
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500 words
Strategic Digital Marketing Campaign Planning Using the RACE Framework: Cambridge Museum of Technology
This Digital Leadership and Disruptive Innovation assessment requires students to act as digital marketing consultants for the Cambridge Museum of Technology and develop a strategic social media campaign focused on the Reach and Act stages of the RACE framework. The campaign is designed to increase awareness of the museum and encourage meaningful interaction using paid and owned content across Facebook and Instagram. Assessment Brief for CW1 (1) The first deliverable is a two-page landscape campaign poster created in Canva. Page 1 focuses on Reach and should present a clear awareness objective, one Facebook paid advertisement mock-up, and one Instagram owned post. Page 2 focuses on Act and should include an engagement objective, one Instagram paid advertisement and one Facebook owned post. Each mock-up must be clearly labelled by platform, RACE phase and media type. Assessment Brief for CW1 (1) Assessment Brief for CW1 (1) The poster is expected to function as a strategic visual board, rather than a website or social feed simulation. It should demonstrate clear visual hierarchy, logical layout, consistent headings, spacing and alignment, and communicate how the Reach and Act strategies connect. The target audience persona should not appear on the poster itself. Assessment Brief for CW1 (1) The second deliverable is a maximum 500-word written rationale. This should define a relevant target audience persona using demographic, psychographic and behavioural characteristics, and explain needs, motivations and online behaviour. The persona should be visually designed and embedded in the written document. Assessment Brief for CW1 (1) The rationale must also justify the Reach content strategy, including platform choice, content format, targeting and budget considerations, and explain the Act engagement strategy, including tactics such as event promotion, interactive posts and comment prompts. Students should also explain how layout, visual structure and calls-to-action support user experience and engagement. Assessment Brief for CW1 (1) The assessment requires application of relevant digital marketing theories and frameworks and at least five credible academic or industry sources, using Cite Them Right Harvard referencing. Suitable evidence can include peer-reviewed journal articles and recognised sources such as Mintel, Statista and industry reports. Assessment Brief for CW1 (1) The marking scheme gives 30% to Reach, 30% to Act, 20% to the written rationale, and 20% to poster design, communication and professional presentation. Assessment Brief for CW1 (1) Assessment Brief for CW1 (1) Overall, the assessment integrates RACE-based campaign planning, paid and owned social media, audience segmentation, persona development, targeting, budget awareness, content strategy, UX principles and professional visual communication within a real cultural-organisation context. Important: the brief explicitly states that the applicable AI category is Category 2 – Proofreading only permitted, meaning AI may be used for proofreading but not for creating assessment content. Assessment Brief for CW1 (1)
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Computer Science / Algorithms / Parallel Computing / Clustering
Parallel Algorithms for Hierarchical Clustering: Single-Link, Minimum Spanning Trees and Parallel Architectures
This research paper investigates parallel algorithms for hierarchical clustering, a clustering technique in which individual data points initially form separate clusters and the closest clusters are repeatedly merged until a hierarchical tree structure, or dendrogram, is formed. The paper reviews important sequential clustering algorithms, surveys previous parallel approaches and proposes parallel methods for several commonly used inter-cluster distance metrics. Prims_algorithm_for_hierarchica… The paper distinguishes between graph-based metrics and geometric metrics. Graph metrics include single-link, average-link and complete-link clustering, while geometric metrics include centroid, median and minimum-variance methods. It also discusses the Lance–Williams updating formula, which provides a general framework for updating inter-cluster distances after agglomeration. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… A major focus is the relationship between single-link hierarchical clustering and the Euclidean minimum spanning tree. The paper explains that the cluster hierarchy for single-link clustering can be obtained from a minimum spanning tree, making minimum-spanning-tree algorithms highly relevant to efficient hierarchical clustering. It presents practical single-link algorithms with O(n²) time complexity and discusses space requirements and nearest-neighbour update properties. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… The paper also examines algorithms for metrics satisfying the reducibility property, where nearest-neighbour chains can be used to efficiently determine which clusters to merge. Minimum-variance and graph-based metrics satisfy this property, while centroid and median metrics do not necessarily do so. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… For more general clustering metrics, the paper describes priority-queue-based algorithms with O(n² log n) sequential time complexity. It then reviews previous parallel work, including parallel implementations of SLINK, Ward’s method and Prim’s minimum spanning tree algorithm. The cited parallel Prim implementation achieves O(n log n) time when sufficient processors are available. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… The core contribution is a set of parallel algorithms for hierarchical clustering on PRAM, butterfly and tree architectures. For single-link clustering, the paper shows how a parallel minimum-spanning-tree approach can be used and reports an O(n log n) running time using n/log n processors. Similar optimal results are described for centroid, median and minimum-variance clustering, while average-link and complete-link methods are more difficult to optimise on local-memory architectures. Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… Prims_algorithm_for_hierarchica… Overall, the paper demonstrates how hierarchical clustering can be accelerated through parallel computation while preserving the computational structure of different clustering metrics. Its main themes include minimum spanning trees, Prim’s algorithm, single-link clustering, nearest-neighbour methods, PRAM computation, parallel data structures and asymptotic complexity analysis. Prims_algorithm_for_hierarchica… Important: because this file is a journal research paper rather than a university assessment brief, fields such as module name, academic level, assignment type and formal word count do not genuinely apply.
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Calculus and Optimisation: Python Implementation of Gradient Descent, Derivatives and Polynomial Regression
This Calculus and Optimisation technical exercise demonstrates the implementation of mathematical and machine-learning concepts using Python. The document is organised as a set of code fragments that must logically work together to perform symbolic calculus, numerical optimisation, physical modelling and polynomial regression. The material uses libraries including NumPy, SymPy, Matplotlib and Scikit-learn, linking mathematical theory with practical computational implementation. Jigsaw_Puzzle_Calculus_Original… A central component is the implementation of gradient descent for linear regression. The supplied function calculates predictions, evaluates prediction errors, computes gradients and updates model parameters iteratively using a configurable learning rate. Mean squared error is recorded during optimisation, and a tolerance-based stopping condition is used to terminate the algorithm when successive cost values change by only a very small amount. Jigsaw_Puzzle_Calculus_Original… Synthetic linear-regression data is generated using a fixed NumPy random seed to support reproducible experimentation. A bias column is added to the feature matrix, initial parameter values are randomly generated, and the custom gradient-descent function is then executed to estimate the intercept and slope of the relationship. Jigsaw_Puzzle_Calculus_Original… The document also demonstrates symbolic differentiation and optimisation using SymPy. A cubic polynomial is defined and differentiated to obtain both its first and second derivatives. Critical points are identified by solving where the first derivative equals zero, while the second derivative is evaluated at each critical point to determine whether the point represents a local minimum, local maximum or saddle point. Jigsaw_Puzzle_Calculus_Original… Jigsaw_Puzzle_Calculus_Original… A further section applies mathematical formulas to projectile motion. Using a specified initial velocity, launch angle and gravitational acceleration, the code calculates both maximum projectile height and horizontal range. This component illustrates how calculus-related mathematical relationships can be translated directly into executable computational models. Jigsaw_Puzzle_Calculus_Original… The final major element explores polynomial regression. Synthetic nonlinear data is generated from a cosine-based function with added random noise. Scikit-learn pipelines are then used to compare polynomial models of degrees 1, 4 and 15. The models are fitted to the synthetic dataset and visualised against the underlying true function, allowing comparison of model complexity and illustrating concepts such as underfitting and overfitting. Jigsaw_Puzzle_Calculus_Original… Jigsaw_Puzzle_Calculus_Original… Overall, the exercise integrates calculus, optimisation, numerical methods and machine-learning modelling through Python. It provides practical experience with differentiation, critical-point analysis, iterative optimisation, mathematical simulation, regression modelling and visualisation. Important: because this file does not identify a university, assessment weighting, academic level, reference style or required word count, those fields should remain Not specified / Not applicable rather than being invented.
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Business Management / Consultancy / Strategic Management
5,000 words
Business Consultancy Project: Strategic Analysis, Stakeholder Evaluation and Evidence-Based Recommendations
This Business Consultancy Project assessment requires students to produce a professional 5,000-word consultancy report addressing a strategically important issue, challenge or problem facing a client organisation. The project must normally continue from the topic and client proposed in the earlier Consultancy Project Proposal, ensuring continuity between the proposal and final consultancy work. The assessment is designed to replicate professional consultancy practice through independent research, critical analysis and the development of actionable recommendations. Copy of Apr 25 Onwards brief_EE… Copy of Apr 25 Onwards brief_EE… The report begins with an Executive Summary, followed by an introduction and company/client overview. Students must define one clear business problem, establish the overall project aim and purpose, and specify the consultancy focus, which may relate to areas such as strategy, human resources, marketing or sustainability. The selected issue should be clearly connected to the organisation’s wider strategic and industry context. Copy of Apr 25 Onwards brief_EE… A dedicated Stakeholder Analysis section requires identification and evaluation of internal and external stakeholders. Students must assess stakeholder interests, influence, expectations, conflicts and power relationships, and are encouraged to apply a framework such as Mendelow’s Matrix. The purpose is to show how stakeholder dynamics influence the consultancy problem and the feasibility of proposed solutions. Copy of Apr 25 Onwards brief_EE… The largest section is Data Analysis and Framework Application, where students critically evaluate secondary evidence and apply two or three relevant management frameworks. Suitable approaches may include SWOT, PESTLE, Porter’s frameworks and the Balanced Scorecard. The analysis should incorporate credible company and industry evidence, Excel outputs, tables or charts where relevant, and connect patterns in the data to strategic, operational or HR implications. Ethical and sustainability considerations should be embedded where appropriate. Copy of Apr 25 Onwards brief_EE… The project concludes with three prioritised and evidence-based recommendations. Recommendations should be practical, justified, risk-aware and linked directly to the findings. Students must explain expected benefits and demonstrate how the proposed actions create strategic value for the client organisation. Copy of Apr 25 Onwards brief_EE… The final assessed section is a 500-word Employability Reflection covering skills developed through the project, application of theory to practice, professional behaviours, personal strengths and weaknesses, career relevance and specific future-development actions. Copy of Apr 25 Onwards brief_EE… Overall, the assessment integrates consultancy problem definition, stakeholder analysis, strategic frameworks, secondary-data interpretation, ethics, sustainability, recommendations and professional reflection within a Masters-level business project. The marking criteria reward criticality, current evidence, intellectual originality, professional consultancy thinking and accurate Harvard referencing. Copy of Apr 25 Onwards brief_EE… One important point: the brief states that the majority of references should come from sources published within the last 6–12 months, so the final project is expected to use very current company, industry and academic evidence. Copy of Apr 25 Onwards brief_EE…
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Data Science / Time Series Analysis / Machine Learning
Time Series Modelling Case Study: Oil Price Forecasting with ARMA and Alternative Models
This Time Series Modelling Case Study requires students to analyse real-world oil-price time-series data and develop forecasting models capable of predicting future values. The assessment combines traditional statistical time-series techniques with an alternative forecasting approach, requiring students to demonstrate practical modelling skills, critical research engagement and evidence-based interpretation of forecasting results. The coursework is completed individually and contributes 40% of the assessment. assing,,, (1) The assessment is divided into three main parts. Part 1 focuses on developing an ARMA-based forecasting model using daily oil-price data covering approximately 2024 to 2026. Students begin with exploratory data analysis and initial visualisation before testing whether the time series is stationary. Where necessary, appropriate transformations or differencing must be applied to obtain stationarity. Students then define an ARMA model and identify suitable p, d and q parameters using an AIC-based model-selection procedure across the parameter ranges specified in the brief. assing,,, (1) Model adequacy must be assessed using diagnostic analysis. Students inspect residuals, generate additional ACF plots, examine residual distributions and evaluate prediction performance using appropriate metrics such as RMSE. The selected model is then used to forecast oil prices 24 months into the future, with appropriate confidence intervals added to communicate forecast uncertainty. assing,,, (1) Part 2 requires students to research and implement an alternative forecasting approach. Suggested examples include LSTM and Prophet, although another appropriate model may be proposed. Students conduct a literature review supporting the alternative method, build and where relevant hyperparameter-tune the model, generate another 24-month forecast, visualise predictions and confidence intervals, and calculate suitable evaluation metrics. This component is intended to demonstrate independent research and the ability to propose an alternative solution rather than relying only on the conventional ARMA approach. assing,,, (1) Part 3 consists of a 6–8 page technical report explaining the modelling process, forecasting results and resulting inferences. The report should provide a critical analysis rather than simply reproducing numerical outputs. Students are expected to explain why results occurred, justify modelling choices, evaluate how those choices influenced performance, compare forecasts with subsequently observed real data where possible, and construct a coherent narrative supported by plots, images, summary statistics and academic literature. Future improvements to the modelling approach should also be critically discussed. assing,,, (1) Submission consists of both the report and working code. The code may be submitted directly or through an accessible Colab or GitHub repository and must reproduce all models, figures and numerical results presented in the report. The assessment allocates 60% of the marks to code and 40% to the report. Within the coding component, modelling and forecasting completion accounts for 40 marks and code quality and annotation for 20 marks. The report is assessed on analysis and inference, methodological justification, comparison of the two modelling approaches, presentation quality, figures and use of appropriate references. assing,,, (1) Key technical expectations include appropriate testing for stationarity, use of methods such as ADF, ACF, PACF and differencing, systematic model selection, forecasting, evaluation and clear comparison between the traditional ARMA model and the chosen alternative approach. Higher-quality work is expected to interpret what the forecasts mean, identify potential improvements and demonstrate sound technical communication rather than merely reporting model outputs. assing,,, (1) Important for the public Reference Library: the brief explicitly states that students must not use generative AI to write the report, and the rubric indicates that AI text-generation use may result in zero marks for the whole assignment. Therefore, the public entry should remain a high-level description of the assessment rather than material intended for direct submission. assing,,, (1)
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Computer Science / Algorithms / Computational Complexity
Modified Merge Sort for Large-Scale Data: Algorithm Analysis, Complexity and Evaluation
This Computational Algorithms and Paradigms assignment critically examines a modified merge sort algorithm designed for large-scale datasets. The work focuses on the computational problem of sorting very large collections of data efficiently while preserving the stability and predictable complexity associated with classical merge sort. The analysed approach replaces recursive processing with an iterative successive-merging strategy intended to reduce stack overhead and improve practical performance on large datasets. Dubba ramesh(up) The first section identifies the underlying computational problem and frames the main research questions. These include how standard merge sort can be modified to improve large-scale performance, whether recursion can be replaced with a non-recursive iterative process, whether the proposed double-merge technique reduces resource consumption, and how its computational performance compares with classical merge sort. Dubba ramesh(up) A technical section then reconstructs the algorithm in pseudocode. The modified process begins with subsequences of size one and repeatedly merges adjacent sorted subsequences, doubling the merge size after each iteration until the entire dataset is sorted. This bottom-up approach removes the recursive decomposition used in conventional merge sort. Dubba ramesh(up) The assignment also identifies the algorithm's principal inputs and outputs. Inputs include the dataset, number of elements, subsequence boundaries and temporary storage required during merging. The resulting output is a fully sorted and stable sequence. Dubba ramesh(up) Complexity analysis shows that the modified algorithm processes approximately n elements across log₂(n) merging levels, resulting in O(n log n) time complexity in both best and worst cases. Because an auxiliary array is used during merging, the reported space complexity is O(n). Dubba ramesh(up) The final critical evaluation highlights the main benefits of the modified approach, including removal of recursive-call overhead, greater stability when processing very large datasets, predictable performance and preservation of merge-sort stability. Its main limitation is the continued requirement for auxiliary memory during the merge operation. The work also notes that the performance advantages are most relevant for large-scale datasets and may be less significant for smaller inputs. Dubba ramesh(up) Overall, the assignment integrates algorithm interpretation, pseudocode extraction, input-output analysis, complexity analysis and critical evaluation within the context of large-scale sorting. Note: this upload appears to be the completed student response rather than the original assessment brief, so the referencing style and exact formal overall word limit are not stated. I would leave the reference-style field as Not specified unless you also upload the official 7COM1078 guideline.
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Probability and Statistics / Data Analysis / Python
Probability and Statistics Jigsaw Puzzle: Probability Calculations and Chi-Square Analysis in Python
This technical Probability and Statistics exercise presents a set of Python code fragments designed to demonstrate basic probability calculations and statistical hypothesis testing. The material is organised as a jigsaw-style collection of code segments, allowing the underlying logical sequence to be reconstructed from variable definitions, probability calculations, observed data, statistical testing and final interpretation. Jigsaw_Puzzle_3_Original_Struct… The first part models a two-bag probability problem. Bag 1 contains four white and two black items, while Bag 2 contains three white and five black items. The code calculates the probabilities of selecting a white or black item from each bag and then uses multiplication rules to determine the probability of drawing two white items, two black items, or one white and one black item across the two bags. Jigsaw_Puzzle_3_Original_Struct… Jigsaw_Puzzle_3_Original_Struct… Jigsaw_Puzzle_3_Original_Struct… A second section demonstrates a chi-square test of independence using an observed frequency table containing grade outcomes for girls and boys across grades A, B, C and D. The data are stored in a NumPy array and analysed using SciPy's chi2_contingency function. The resulting chi-square statistic, p-value, degrees of freedom and expected frequencies are calculated and displayed. Jigsaw_Puzzle_3_Original_Struct… Jigsaw_Puzzle_3_Original_Struct… The final fragment applies a conventional significance threshold of α = 0.05. If the p-value is greater than 0.05, the code reports that the null hypothesis should not be rejected; otherwise, it concludes that a statistically significant difference exists. Jigsaw_Puzzle_3_Original_Struct… Overall, the document demonstrates core statistical-programming concepts including probability rules, contingency tables, chi-square analysis, expected frequencies, p-value interpretation and hypothesis testing using Python, NumPy and SciPy. Important: because this file does not identify a university, module, academic level, academic year, assignment brief, formal word count or referencing system, I would leave those fields as Not specified rather than guessing.
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Cyber Security / Applied Cryptography / Secure Systems Design
2,500 words
Secure Property Contract Exchange: Cryptographic Protocol Design, Threat Modelling and Post-Quantum Readiness
This Applied Theory of Cyber Security and Secure Design coursework places students in the role of a cyber security consultant engaged by Hackit & Run LLP, a legal firm specialising in UK and international property transactions. The firm wishes to implement a secure digital system for handling, exchanging and legally signing property contracts. Students must design and evaluate a secure communication protocol supporting interactions between the buyer’s solicitor, the seller’s solicitor and the buyer while addressing both first-time communications and previously established secure relationships. 11b17febb9eeb4570f76f6ca95a831a… Section A – Cryptographic Protocol Design, worth 45%, requires a complete secure communication protocol. Students must explain how trust is initially established, how later communications can be simplified without weakening confidentiality, integrity or availability, and how the buyer can digitally sign a contract in a manner enforceable under UK law. The design must justify specific cryptographic algorithms for functions such as key exchange, bulk encryption, digital signatures and hashing. The protocol must be presented through both a sequence diagram showing message flows and cryptographic operations and pseudocode explaining the key algorithmic stages. 11b17febb9eeb4570f76f6ca95a831a… Section B – Threat Modelling, worth 20%, requires a focused analysis using the STRIDE methodology. Students identify three realistic threats from different STRIDE categories and analyse the attack vector, asset at risk and potential effect on the legal transaction. Each threat must then be connected back to specific protocol defences, with residual risks acknowledged where controls cannot provide complete mitigation. The guidance encourages consideration of issues such as social engineering, insider threats, key-management failures and availability risks in addition to purely cryptographic attacks. 11b17febb9eeb4570f76f6ca95a831a… Section C – Security Evaluation Against Standards, worth 15%, requires students to evaluate the proposed system against a recognised cybersecurity standard or framework. Options include ISO/IEC 27001:2022, Common Criteria (ISO/IEC 15408) and the OWASP Application Security Verification Standard. Students select three or four directly relevant controls or requirements, assess whether the proposed design satisfies them, identify gaps and recommend specific improvements. 11b17febb9eeb4570f76f6ca95a831a… Section D – Post-Quantum Readiness and Critical Reflection, worth 15%, examines how a future quantum-capable adversary could affect the protocol. Students identify vulnerable cryptographic components, discuss the NIST Post-Quantum Cryptography standardisation programme, and examine replacement algorithms such as ML-KEM for key establishment and ML-DSA for digital signatures. They must also evaluate a hybrid migration strategy combining classical and post-quantum algorithms, considering performance overhead, backward compatibility and the legal admissibility of post-quantum digital signatures. 11b17febb9eeb4570f76f6ca95a831a… The remaining 5% evaluates professional report quality, logical structure, technical language, integration of diagrams and consistent CUHarvard referencing. Higher-quality work is expected to demonstrate a sophisticated trust model, clear traceability between threats and controls, precise standards mapping, practical security recommendations and well-evidenced analysis of post-quantum migration. 11b17febb9eeb4570f76f6ca95a831a… Important for the public Reference Library: the brief states that the assessment document is intended only for Coventry University Group students and must not be passed to third parties or posted on any website. Therefore, publish only an original high-level description such as the overview above; do not upload or reproduce the original assignment brief publicly. 11b17febb9eeb4570f76f6ca95a831a…
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3,000 words
ParkaLot Enterprise Parking Garage Management System: Software Analysis, Design and Prototype Development
This enterprise software engineering project requires students to analyse, design and prototype a centralised parking garage management system for ParkaLot Group, a UK operator of multi-storey parking facilities. The existing organisation relies heavily on manual processes, local spreadsheets and simple barrier-based vehicle counts, resulting in limited real-time occupancy information, inconsistent reservation arrangements, decentralised billing and reduced ability to optimise parking capacity and revenue. COMP1471 CW 2526 (1) The proposed system supports ParkaLot’s wider digital transformation by integrating customer registration, reservations, parking-space allocation, occupancy monitoring, contracts and billing. Customers can check availability and reserve parking through an online portal, while frequent and corporate users can establish recurring arrangements or block reservations. License-plate recognition and individual parking-space sensors enable automated access control and real-time occupancy tracking. COMP1471 CW 2526 (1) Additional functionality includes centralised electronic billing, dynamic pricing, promotional schemes and predictive decision-making for controlled overbooking. Historical usage data may be analysed to estimate no-shows, early departures and overstays, while operational dashboards support staffing, pricing and capacity-management decisions across the garage network. COMP1471 CW 2526 (1) Development is undertaken in two phases. The first uses structured analysis and design, requiring an Entity Relationship Diagram, Data Flow Diagram including a context diagram, and implementation of a prototype database. The second expands the solution using object-oriented analysis and UML, with emphasis on adaptable and reusable software design. COMP1471 CW 2526 (1) The final report covers the software-engineering **5 Ps—Problem, Process, Project, Product and People—**alongside ERD and DFD models, UML use cases, at least three sequence diagrams, a detailed class diagram and application of design patterns such as GRASP. Students must also submit prototype evidence, source code, personal reflection, peer assessment and work-contribution documentation. COMP1471 CW 2526 (1) Overall, the assessment integrates requirements engineering, structured modelling, object-oriented design, database development, design patterns, software project management, implementation and acceptance testing within a realistic enterprise-system case study. Overview word count: approximately 360 words. AI-use note: the brief permits Levels 1–4 of generative-AI use, including research and exploration at Level 4, but all final submitted text, code, diagrams and designs must be the students’ own work. Level 4 use requires disclosure, an appendix of prompts/outputs and reflective commentary. COMP1471 CW 2526 (1)
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Software Engineering / Enterprise Systems Development
3,000 words
Enterprise Software Engineering Development: ParkaLot Parking Management System Analysis, Design and Prototype
This Enterprise Software Engineering Development assessment is based on the ParkaLot Group, a fictional operator of multi-storey parking garages across major UK cities. The organisation currently relies on fragmented manual processes, basic barrier-based vehicle counting, local spreadsheets, on-site payment and inconsistent customer access arrangements. Students act as software engineering consultants and are required to analyse these operational weaknesses and design a centralised enterprise parking management system capable of supporting reservations, customer accounts, vehicle identification, billing, real-time occupancy monitoring, dynamic pricing and management reporting. COMP1471 CW 2526 The proposed ParkaLot platform is intended to integrate customers, parking spaces, reservations and billing across the garage network. Planned functionality includes online registration and reservation, recurring and corporate parking arrangements, licence-plate recognition, automated space allocation, sensor-based occupancy tracking, centralised monthly billing, electronic payments, promotional pricing and predictive overbooking. The system must also provide dashboards and historical reporting to assist management with capacity planning, staffing, pricing and operational decision-making. COMP1471 CW 2526 The coursework is completed in two main development phases. Phase 1 – Structured Analysis and Design requires an Entity Relationship Diagram representing the logical data model, a Data Flow Diagram including a Level 0 context diagram, and implementation of a prototype database. Phase 2 – Object-Oriented Development extends the system using object-oriented analysis, design principles and UML, with substantial business and user-interface functionality implemented using suitable OO technologies. COMP1471 CW 2526 The final report contains analysis of the 5 Ps of software engineering: Problem, Process, Project, Product and People. Students discuss the business problem and commercial risks, justify the development methodology followed, define resources and budget, document project artefacts and requirements, and identify the main stakeholders involved in the project. The technical design section includes the ERD, DFD, UML use-case model, at least three sequence diagrams, a detailed class diagram and discussion of design patterns. COMP1471 CW 2526 Students must additionally submit a functioning prototype that reflects the design and participate in acceptance testing and a live demonstration. Individual students are questioned on both theoretical and technical aspects of the submitted system. The assessment also evaluates group contribution, peer and self-assessment, personal reflection, research quality, communication and professional teamwork. COMP1471 CW 2526 The weighting places substantial emphasis on technical design and implementation: the UML design is worth 24 marks, the software prototype 15 marks, design patterns 6 marks, and acceptance testing/demonstration 25 marks. This makes the coursework strongly focused on demonstrating the relationship between requirements analysis, software architecture, UML modelling, implementation quality and working enterprise-system functionality. COMP1471 CW 2526
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Data Science / Data Analytics
Airline Passenger, Ticket Price and Revenue Analysis Using Python
This applied Data Science project requires students to use Python to analyse passenger demand, ticket prices and airline revenues across the period 2021–2023. Two datasets are provided: one containing daily passenger counts and revenue or average-price information for 2021 and 2022, and another containing a representative sample of individual journeys made during 2023. The datasets may include domestic, European and intercontinental routes as well as standard/economy and business/club travel classes. 202526_SmallProject_semB Students must develop Python code that reads the assigned datasets and produces a series of analytical visualisations. A core requirement is to plot daily passenger numbers for economy and business classes across all three years, combining scatter plots with smoothed trend lines. The smoothing must be calculated using the first eight terms of a Fourier series through the supplied scrfft.py module. 202526_SmallProject_semB Further analysis examines changes in average ticket prices, including monthly comparisons across 2021, 2022 and 2023, together with annual average prices that incorporate revenue generated from additional services such as seat reservations and extra baggage. 202526_SmallProject_semB A fourth analysis is personalised according to the final digit of the student's ID. Depending on the allocated task, students may investigate weekly journey distributions, seasonal travel patterns, price-versus-distance relationships, business and economy class behaviour, additional-service revenues, weekend journeys or linear relationships between selected variables. Three additional numerical values, labelled X, Y and Z, must also be calculated according to the assigned scenario. 202526_SmallProject_semB The final report must include four figures, relevant mathematical formulae and a critical discussion of the findings. Students are expected to interpret trends in passenger numbers, prices, revenues, seasonal patterns and airline profitability rather than simply presenting calculations. The report is limited to five A4 pages, while the Python source code and report are submitted separately. 202526_SmallProject_semB Overview word count: approximately 330 words. Note: the university name is not printed directly in the visible assignment heading, but the submission instructions use a herts.ac.uk module-leader address and StudyNet/Canvas, which identifies the institution as the University of Hertfordshire. 202526_SmallProject_semB
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Digital Forensics / Cyber Security
3,000 words
Digital Forensics Investigation of a USB Device: Evidence Acquisition, Analysis and Reporting
This Digital Forensics assessment requires students to undertake a simulated professional investigation of a USB storage device while acting as a digital forensic trainee for a fictional forensic-services organisation. The nature of the suspected wrongdoing is initially unknown, requiring the investigator to apply appropriate forensic methodologies, tools and analytical techniques to identify suspicious activity, recover relevant artefacts and determine whether evidence of malicious or unauthorised behaviour exists. 7070SCN_Assessment Brief_2526MA… The investigation begins with authorisation, evidence handling and chain of custody. Students must demonstrate secure receipt and management of the USB device, operate within the authorised scope of the investigation and maintain records covering each stage of the evidence lifecycle. Forensic acquisition requires use and validation of a software write blocker, creation of bit-for-bit forensic images and cryptographic hashing to demonstrate that working and evidential copies maintain integrity. 7070SCN_Assessment Brief_2526MA… The analytical stage involves examination of the working forensic image using appropriate digital-forensic tools. Students investigate file-signature mismatches, password-protected files, registry artefacts, USB history, user activity, metadata and timeline relationships. Where suspicious executable files are discovered, static and/or dynamic malware analysis may be undertaken. The investigation can therefore span documents, images, applications, executables and registry hives. 7070SCN_Assessment Brief_2526MA… Students must maintain objective and chronological forensic case notes documenting evidence acquisition, preservation, analysis and interpretation. These records should support reproducibility and potential evidential admissibility. The final forensic report summarises findings, explains and justifies the tools and methodologies used, records integrity-verification results, discusses relevant legal, ethical and professional principles and provides appropriate recommendations for further action. 7070SCN_Assessment Brief_2526MA… The assessment also encourages advanced forensic analysis where relevant, including OSINT, password recovery or decryption, data carving, regular-expression searching, advanced registry analysis and static or dynamic malware investigation. Professional practice is assessed through adherence to recognised forensic methodologies, industry best practice, legal and ethical obligations, chain-of-custody records and evidence-handling procedures. 7070SCN_Assessment Brief_2526MA… Overall, the coursework integrates forensic acquisition, evidence preservation, artefact analysis, advanced investigation techniques, professional documentation and legally defensible reporting within a realistic digital-forensics case-study environment. Important for your public Reference Library: this brief explicitly states that it is for Coventry University Group students' own use and must not be passed to third parties or posted on any website. 7070SCN_Assessment Brief_2526MA… So use the metadata and an original high-level overview like the one above, but do not upload or publicly reproduce the assessment brief itself.
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Software Engineering / Object-Oriented Programming / Java Development
Java Group Exercise Booking and Management System for Furzefield Leisure Centre
This software-development coursework requires students to design and implement a Java-based booking and management system for Furzefield Leisure Centre (FLC). The proposed system manages member bookings for group exercise lessons delivered on Saturdays and Sundays. Exercise types can include Yoga, Zumba, Aquacise, Box Fit and Body Blitz, with each lesson accommodating a maximum of four members and carrying an exercise-specific price. 7COM1025 Coursework Explanation… The application must enable members to search the lesson timetable either by day or exercise type and make bookings subject to capacity constraints. Members may book multiple lessons, but duplicate bookings for the same lesson are prohibited. Existing bookings can be changed when capacity is available in the replacement lesson or cancelled before attendance. Successful changes must retain the existing booking ID while releasing the place held in the original lesson. 7COM1025 Coursework Explanation… 7COM1025 Coursework Explanation… After attending a lesson, members can provide a written review and a numerical rating from 1 to 5. Booking statuses should distinguish booked, changed, attended and cancelled reservations. The system must also generate management reports showing attendance and average lesson ratings and identify the exercise type producing the highest income, while listing income generated by each exercise category. 7COM1025 Coursework Explanation… 7COM1025 Coursework Explanation… Students must design at least eight weekends of timetable data, equivalent to 48 lessons, covering at least four exercise types. The program should be self-contained and does not require an external database or security protocol. 7COM1025 Coursework Explanation… The software-engineering component requires a UML class diagram, Java implementation, JUnit testing, version-control evidence and consideration of design principles, design patterns and refactoring. Students submit a PDF report containing the UML diagram and repository evidence, a ZIP containing source code, tests and an executable JAR, and a screen-recording demonstrating the final system. 7COM1025 Coursework Explanation… 7COM1025 Coursework Explanation… Overall, the coursework assesses practical object-oriented software development through system modelling, implementation, validation and reflective documentation. The marking allocates 40 marks to system functionality, 30 to design and implementation, 10 to UML, 10 to JUnit testing, 5 to version control and 5 to report quality. 7COM1025 Coursework Explanation… Note: the uploaded material identifies the code 7COM1025 but does not state the formal module title. I would therefore keep Module name = Not specified rather than inventing one.
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Cybersecurity / Security Operations
Catnip Games International: SOC Automation and Incident Response Platform
This cybersecurity project presents the design and implementation of a prototype Security Operations Centre (SOC) automation and incident-response platform for Catnip Games International. The scenario addresses security challenges affecting a gaming organisation operating more than 300 Linux servers across two data centres, including credential-stuffing bot attacks, compromised player accounts, phishing campaigns and delayed coordination during security incidents. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete The proposed solution integrates TheHive 5, Cortex 3, Elasticsearch, Cassandra and Python-based automation, with MISP explored for threat-intelligence integration. TheHive functions as the central incident and case-management platform, Cortex provides automated observable analysis, Elasticsearch supports search and log storage, Cassandra provides persistent case and alert storage, and Python scripts automate alert ingestion and workflow activities through REST APIs. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete Implementation includes environment configuration, Docker deployment, API integration, automated alert generation, incident-response playbooks, KPI monitoring and backup procedures. Three attack scenarios are modelled: bot attacks, account takeover and phishing. Alerts are automatically ingested into TheHive, converted into cases and processed through analyst triage, investigation and resolution workflows. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete The project also develops structured response playbooks covering triage, containment, investigation, recovery and post-incident actions for each security scenario. Operational metrics are visualised through a KPI dashboard measuring alert volumes, response times, Mean Time to Detect (MTTD), Mean Time to Respond/Resolve (MTTR) and platform availability. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete Overall, the work demonstrates practical application of SOC architecture, security automation, incident management, threat analysis, containerised infrastructure, API-based integration, operational metrics and cyber-response procedures within a realistic gaming-industry security scenario. Catnip_Games_SOC_Complete Overview word count: approximately 330 words. Important before putting the presentation on a public Reference Library: redact any API keys/authentication tokens and other live credentials shown in the technical slides. The presentation includes API-key material in the Cortex and Python automation sections, so those credentials should also be revoked/rotated if they were ever active. Catnip_Games_SOC_Complete Catnip_Games_SOC_Complete
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Leadership and Professional Development
2,500 words
Leadership Mindset – Professional Development Portfolio
This assessment is a Leadership Mindset Professional Development Portfolio designed to encourage students to think strategically about their career development, align their professional goals and demonstrate leadership potential. The assessment focuses on self-awareness, strategic planning, professional behavioural skills and the ability to develop an ongoing process of personal and professional growth. Students are required to complete a Portfolio through PebblePad, equivalent to 2,500 words. The portfolio is assessed on a Pass/Fail basis and students must complete all required sections before downloading the completed portfolio and submitting it through Turnitin. The portfolio does not require academic referencing because it is a self-reflection and professional development assessment. The portfolio consists of several key components, including a personal SWOT analysis, evidence of communication requesting feedback, a Personal Development Plan (PDP), a CV and a cover letter. The SWOT analysis requires students to identify their strengths, weaknesses, opportunities and threats in order to understand their current skills, identify development gaps and recognise opportunities for improvement. Students must also reflect on the Professional Development Pyramid or another suitable professional development model and select three behavioural skills or competencies they wish to develop. Examples include strategic thinking and leadership. Feedback must be requested from four to six people from the student's personal and professional network, such as family members, friends, peers, mentors, employers or colleagues. This feedback is then used to support the student's development priorities. The action-planning section requires students to reflect on the feedback received and identify three development priorities or goals. For each priority, at least two SMART actions must be established. The action plan should include specific steps, timelines and required resources, while also identifying potential obstacles and explaining how these obstacles may be addressed. The goals and actions should demonstrate a clear connection between the student's self-reflection, feedback and professional development objectives. The final reflection considers the value of the PebblePad portfolio process in shaping personal and professional growth. Students are expected to demonstrate an in-depth understanding of self-development and explain how their development process can be reviewed, revised and adapted for continuing professional growth. The assessment learning outcomes focus on reflection on personal strengths and areas for improvement, advanced critical thinking, problem-solving and decision-making, intercultural communication, inclusivity and sustainability, interview and presentation competencies, and the ability to articulate an adaptable self-development process. The marking criteria emphasise self-reflection, clarity of goals, strategic action planning, persuasive understanding of professional development, and clear and professional presentation.
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Integrated Communications
2,000 words
CW2 Communications Engagement Report – Client Stream
This assignment requires students to produce an individual 2,000-word Communications Engagement Report in the form of an engagement communications campaign for Stream. Stream is a collaboration between 16 UK water companies, supported by industry and civil society partners including the Open Data Institute, with the aim of unlocking the potential of water-sector data to benefit customers, society and the environment. The organisation has established data-sharing infrastructure designed to enable data to be used to generate insights, support innovation, improve decision-making and contribute to greater transparency across the water sector. The central focus of the assignment is to develop a communications campaign that attracts and engages the research and academic community. Stream has identified postgraduate and postdoctoral students, together with relevant university faculty leads, as an important priority audience because of their potential to transform published water-sector data into valuable research insights, innovative products and services. Relevant academic departments may include computer science, engineering, mathematics, environmental science, social science, town planning and business development. Students are expected to consider how this audience can be reached, segmented and prioritised according to its interest and willingness to engage with Stream. The proposed campaign should build awareness of Stream, communicate the value of accessing and using water-sector data, and encourage longer-term engagement between Stream, universities and students. Existing communication channels include LinkedIn, the Stream website and communications distributed through delivery partners such as the Open Data Institute and Aiimi, as well as Ofwat. Key campaign opportunities include Open Data Day in March and Open October in mid-October. These events should be considered as important campaign moments while also being integrated into a longer-term communications programme. The report should include an introduction and background to Stream, including brand history, market position, competitive analysis, the need for an engagement communications campaign and relevant market research. It should establish short-, medium- and long-term communication objectives with clear timeframes, define the target audience, and apply an appropriate theoretical framework to develop the communication strategy. Students must provide four recommended communication pieces supported by detailed rationale, together with a Gantt chart showing campaign timings and a clear campaign measurement approach. The report should conclude with a summary of the overall proposal. The assessment requires critical application of communication theories and concepts, research evidence and relevant literature. Students must demonstrate analysis, evaluation and justification rather than simply describing communication activities. A minimum of 15 high-quality references is required, including at least eight journal articles, using Cite Them Right Harvard referencing. The report is assessed on presentation and structure, intellectual curiosity and referencing, content and application, campaign integration, discussion, conclusion, recommendations, campaign timeframes and measurement.
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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 Warehousing and Big Data
Data Warehousing and Big Data – Inventory Management Data Warehouse
This individual coursework for CS7079 Data Warehousing and Big Data requires students to design, implement and test a data warehouse based on a business case scenario and then export and migrate data to a Big Data platform for further processing. The assessment focuses on the inventory management business process of ABC Consumer Electronics Outlet Ltd, a multi-channel consumer electronics retailer operating from six stores around London and conducting online business across the UK and Europe. The company manages more than 10,000 products across approximately ten categories and more than 200 brands. The company already uses cloud-based and business applications including Vend, Linnworks and Xerox, which generate large volumes of transactional data. However, these datasets are stored separately by the individual applications, making it difficult for managers to produce integrated reports and perform analysis to support business decision-making. A business analyst has therefore recommended the development of a data warehouse capable of meeting the company's reporting and analytical requirements. For this coursework, the solution is focused specifically on the inventory management business process. The inventory management case involves three main business activities: sending purchase orders to suppliers when stock reaches minimum levels, receiving purchase orders and storing stock in appropriate locations, and controlling and maintaining stock levels including adding new products and adjusting existing stock. The required analysis includes daily stock levels for the previous month, weekly identification of products at minimum stock levels, analysis of stock levels by brand, product type and supplier, daily and weekly sent and received stock orders, and analysis of received stock orders by supplier and month. Students must analyse and design a dimensional data model that represents these business activities. This includes defining the grain of three central fact tables, identifying appropriate dimensions, defining dimension attributes and fact measures, and producing simple star schemas showing the relationships between fact tables and dimensions. The design must be justified according to the available data sources and the reporting and analysis requirements. The implementation stage requires students to create the relational database using Microsoft SQL Server Management Studio. Students must create the database, dimension tables and fact tables, establish appropriate primary-key and foreign-key constraints, and demonstrate implementation and testing through SQL commands and their results. Test data must then be populated into the data warehouse. The Big Data component requires migration of test data from the data warehouse to an Apache Hadoop platform using the Hortonworks Data Platform. Students must export the data warehouse data to an external data file, migrate the file into Apache HDFS, create a suitable data structure for loading the data into Hive, and demonstrate Apache Pig for manipulating the loaded data. Implementation and testing of the Big Data storage environment must also be demonstrated through commands and results. The coursework concludes with a personal reflective section in which students discuss what they have learned throughout the overall coursework and the challenges encountered during the process. The final submission is expected to be a well-written, structured and well-presented report combining data warehouse design, database implementation, testing, Big Data migration and reflective learning.
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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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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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Security of Emerging Connected Systems
2,000 words
Security Evaluation – Secure Design, Security Audit and IoT Security Recommendations
This individual coursework for the Security of Emerging Connected Systems module requires students to prepare a 2,000-word technical report evaluating secure design, security auditing and security recommendations for an organisation developing Internet of Things (IoT) devices and systems for home and workplace environments. The assessment is worth 10 credits and requires students to provide practical and evidence-based guidance to the client’s software development team. The report is assessed across secure design and development methodology, security audit methodology, security recommendations and overall report structure. The first major section addresses Secure Design and Development Methodology. The client wants to incorporate secure design principles into its software development workflow and therefore requires an overview of possible secure design processes relevant to IoT. Students must evaluate the strengths and weaknesses of different approaches and provide a justified recommendation for a process that would be appropriate for the client. The emphasis is on integrating security into the design and development of systems rather than treating security as a separate activity after development. The second section focuses on Security Audit Methodology. The client wants to complement its secure design process with a security audit of the final developed system. Students must provide a practical guide explaining how a security audit could be performed, including the overall testing methodology and the purpose of each stage. The brief identifies methodologies such as PTES and OWASP as examples. Students are also expected to discuss different approaches and evaluate their respective strengths and weaknesses. The third section concerns Security Recommendations and requires students to demonstrate the implications of strong secure design and auditing through an IoT security case study. Students must research a security vulnerability affecting an IoT device, explain the vulnerability and identify where the security flaw was introduced. The report must then examine which parts of the secure design and audit processes were not implemented correctly and evaluate the resulting impact on the security of the product. The report is intended for a technical audience, specifically the client's software development team. Students are expected to use an appropriate technical structure and language, support their arguments and analysis with references, and use APA referencing. The assessment also encourages appropriate diagrams to support the written content. The report structure component accounts for 10% of the assessment, while Secure Design and Development Methodology, Security Audit Methodology and Security Recommendations each account for 30%. The coursework assesses learning outcomes relating to defence-in-depth solutions for technical internet security vulnerabilities, secure private networks for IoT and BYOD, and current research and technological advances in network security. These outcomes connect the assignment to practical IoT security engineering, secure development, security auditing and emerging network-security practices.
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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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International Marketing and Brand Management
6,000 words
International Marketing and Brand Management – International Brand Expansion Project
This individual project report for the International Marketing and Brand Management module focuses on analysing a selected brand and developing a strategy for its expansion into a new international market. Students must select a brand that is currently available in a limited number of countries or within a particular region and that has a physical market offering. The completed case study must be between 4,000 and 6,000 words, with 6,000 words specified as the maximum. The first part of the assignment focuses on Brand Analysis. Students are required to introduce the selected brand and examine its brand portfolio and geographical availability. The analysis must also consider the brand’s elements and evaluate its brand equity using Keller’s Customer-Based Brand Equity (CBBE) model. Students must additionally identify and analyse an appropriate brand mantra. These elements are intended to provide a comprehensive understanding of the brand’s existing market position and identity. The second part examines potential international markets for the selected brand. Students must conduct SLEPT analyses of three culturally distinct markets that the brand could potentially enter. Each market must also be assessed through competitor analysis. This section requires students to consider the wider market environment and competitive conditions when evaluating potential international expansion opportunities. The third part develops the Strategy for Market Entry. Students must select and justify one new international market for the brand to enter and recommend an appropriate market entry strategy. The report must also provide recommendations regarding standardisation or adaptation using a marketing mix framework. In addition, students must identify the intended Points of Parity (POP) and Points of Differentiation (POD) that would support the brand’s positioning in the selected international market. The assignment requires students to integrate relevant academic models and theories into the brand case rather than simply describing them. Sources used to support models, theories, claims and arguments must be appropriately referenced using Harvard referencing, both through in-text citations and in the final reference list. Students are also encouraged to use appropriately referenced images and figures to illustrate their case study. Assessment weighting is divided equally across the three substantive sections, with Brand Analysis accounting for 30%, International Market Analyses for 30%, and Strategy for Market Entry for 30%. The remaining 10% assesses presentation, including the range and quality of sources, Harvard referencing, clarity of writing and presentation, and quality of discussion.
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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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Secure Design and Development
2,000 words
Secure Design and Development – PixelForge Nexus (UITS)
This assessment for Coventry University’s Secure Design and Development module requires students to design and develop a functional secure online system with the aid of a Large Language Model (LLM). The assignment is based on a practical scenario involving Creative SkillZ LLC and its proposed “PixelForge Nexus” system. The submission combines a functional prototype, an individual 2,000-word report, source code hosted in the Coventry University GitHub environment, and a video report demonstrating the completed prototype. The PixelForge Nexus prototype is intended to provide secure project management and basic asset and resource management for a game-development environment. Core functionality includes adding and removing projects, viewing active projects, assigning developers to projects, allowing developers to view their assigned projects, uploading project documents, and allowing authorised users to access documents associated with their projects. The system must implement privilege separation between Admin, Project Lead and Developer roles. Security is a central requirement of the assignment. Administrators are responsible for managing projects and user accounts, Project Leads can assign developers and upload project documents, while Developers can view assigned projects and associated documents. The system must include a robust login mechanism with secure password hashing and storage, with Multi-Factor Authentication recommended as an additional security measure. Proposed pages include Sign In/Register, a role-based User Dashboard, Account Settings and a Project Details page. The practical assessment evaluates four major areas: System Design, Security Testing and Analysis, System Development, and Formal Methods. System design requires consideration of secure design principles and their application to the development lifecycle. Security testing requires critical evaluation of security techniques, identification of issues and proposed mitigation measures. System development requires a functional prototype that follows the proposed design and considers legal and ethical requirements. Formal methods require a behavioural model and appropriate verification techniques to establish whether the system meets its specification. The individual report must document the methods and techniques used to develop the prototype and discuss the stages of the development lifecycle, including specification, design and development. It must also explain the deployment and testing approach, limitations of the prototype, possible improvements, security techniques and the formal model used. The submission must include links to the Coventry University GitHub repository and Microsoft OneDrive video, while the required appendix contains the LLM prompt history and other resources used with APA-style referencing.
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Principles of Data Science
2,000 words
Principles of Data Science – Data Analysis Portfolio
This portfolio assignment for the Principles of Data Science module at Coventry University requires students to analyse the Global Life-Work Balance Index 2025 dataset using statistical and data science techniques in R. The dataset ranks 60 countries according to life-work balance using factors including statutory annual leave, paid maternity leave, sick leave, healthcare, public safety, public happiness, LGBTQ inclusivity and average working hours per employee. The assignment has a 2,000-word equivalent limit, excluding the reference list and output. The portfolio consists of two main tasks. Task 1 is a group task involving multivariate data analysis. Students must use R to perform Principal Component Analysis (PCA) and Cluster Analysis on the dataset. For PCA, students analyse quantitative variables, produce and interpret relevant visualisations such as screeplots, biplots and loadings plots, and investigate the effects of Region and Healthcare System. The PCA analysis also requires comparison of the overall dataset with countries from Europe. The cluster analysis component requires students to cluster both countries and variables using different distance metrics and hierarchical clustering methods. Students compare methods such as Manhattan and Euclidean distances and single linkage and Ward’s method, present comparisons in compact tables, and interpret relevant dendrograms. They must then compare the conclusions obtained from PCA and Cluster Analysis, identifying common insights and apparent conflicts and discussing the extent to which the results are explainable rather than simply interpretable. Task 2 is an individual task focusing on Exploratory Data Analysis and Linear Models. Students create a scatter matrix using ggpairs(), investigate strongly correlated variables, and identify quantitative variables that may help predict Region for European and Asian countries. They then develop and critically assess linear regression models for predicting Score, including models based on employment variables and broader quantitative predictors. Model comparison and selection use concepts including AIC, while diagnostic plots are used to identify countries requiring further investigation. The individual task also requires students to use European Life-Work Balance Index 2023 data to make predictions for European countries not included in the 2025 dataset and to construct a Residuals versus Fitted Values plot. Finally, students must combine the conclusions from their individual linear modelling work with the PCA and Cluster Analysis findings to identify specific discoveries about the variables and countries in the dataset. R code, output and relevant plots must be included directly within the reports. The assignment encourages use of the R tidyverse and requires appropriate referencing of sources. The brief specifies APA-style referencing for the individual and group work. It also states that generative AI may be used for inspiration but not for generating answers or analysing the datasets, and any permitted AI use must be acknowledged and documented.
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Emerging Technology and Cloud Computing
5,000 words
Emerging Technology and Cloud Computing – SafeCloud Project
This MSc Management coursework for BPP University’s Emerging Technology and Cloud Computing module is a 5,000-word formal business report based on the SafeCloud project at AlwaysUp Ltd., a manufacturing company specialising in power-electric equipment for buildings and critical installations. The assignment examines how emerging technologies, Big Data and cloud computing can support AlwaysUp Ltd.’s international expansion, real-time equipment monitoring, personalised preventive maintenance, data-driven decision-making, and secure management of equipment and client information. The company is seeking to expand from the UK into European markets through distributor partnerships and ultimately achieve global reach. The report requires the identification and critical evaluation of two emerging technologies that can improve AlwaysUp Ltd.’s support and equipment-care services. Students must evaluate the benefits and limitations of each technology within a manufacturing context and use real-world examples to support the analysis. The assignment specifically assesses the ability to demonstrate a comprehensive understanding and critical evaluation of emerging technologies in business. The second task focuses on designing and evaluating a cloud-based Big Data architecture that integrates the two selected emerging technologies. The proposed architecture must include an architecture diagram and should be evaluated in terms of scalability, security, cost-effectiveness, real-time data processing and decision-making. The solution should address AlwaysUp Ltd.’s business requirements and enable the collection, storage and analysis of equipment-related data. The third task examines data protection, ethical considerations, project risks and resource requirements associated with implementing the proposed solution. This includes consideration of data protection and ethical issues arising from the selected technologies, implementation risks, and the human, technological and other resources required. The fourth task analyses the strengths and weaknesses of the combined emerging technologies and Big Data architecture and considers their application to AlwaysUp Ltd.’s business strategy. The report must conclude with a proposed route forward based on the findings. The required report structure consists of an introduction of approximately 500 words, four main tasks of approximately 1,000 words each, a conclusion of approximately 500 words, Harvard-style references and optional appendices.
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Consultancy Project
1,464 words
Enhancing Sustainable Supply Chain Practices through Digital Transformation: A Case Study of Unilever Plc
This consultancy project proposal examines how digital transformation can enhance sustainable supply chain practices at Unilever Plc. Unilever is presented as a multinational fast-moving consumer goods organisation operating across more than 190 markets, with a complex global supply chain and sustainability commitments linked to the United Nations Sustainable Development Goals. The proposal focuses on the challenges associated with achieving supply chain transparency, managing fragmented sustainability data, and balancing sustainable sourcing and operational costs. The project investigates how emerging digital technologies, particularly blockchain, the Internet of Things (IoT) and Artificial Intelligence (AI), could support greater transparency, traceability, operational efficiency and sustainability within Unilever's supply chain. The organisational analysis identifies issues including the complexity of tracing raw materials across multi-tier supply chains, fragmented procurement and sustainability information systems, and the tension between sustainability investments and short-term operational costs. The proposal also considers infrastructure readiness, data security and employee upskilling as factors affecting digital transformation. The research aims to examine how digital transformation technologies could improve sustainable supply chain planning at Unilever while supporting long-term business and environmental goals. Three objectives are established: examining sustainability challenges affecting Unilever's global supply chain, assessing how blockchain, IoT and AI could improve transparency, traceability and efficiency, and proposing strategic recommendations for integrating digital innovation into Unilever's sustainability framework. The central research question examines how digital transformation can contribute to an ethical, transparent and sustainable supply chain while maintaining operational efficiency. A qualitative exploratory case-study research design is proposed. The main emphasis is on secondary data, including Unilever's annual reports, sustainability information, digital transformation publications, company news, industry articles and analyst reports. Where feasible, primary data may be collected through semi-structured expert interviews and a short qualitative questionnaire. The proposed analysis includes thematic analysis, document review and descriptive statistics using relevant secondary numerical data. Validity is supported through triangulation, while reliability is addressed through consistent coding and an audit trail. The proposal also addresses ethical considerations, including research integrity, transparency, confidentiality, informed consent, anonymity, GDPR requirements, plagiarism avoidance, Harvard referencing and potential corporate bias or greenwashing. Overall, the project explores the potential contribution of digital innovation to Unilever's sustainability objectives and the wider responsible digitalisation of the FMCG supply chain.
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Consultancy Project
1,500 words
Consultancy Project Proposal
This assessment requires students to develop a professional Consultancy Project Proposal addressing a current organisational issue or business challenge. The assessment consists of a 1,500-word individual project proposal worth 80% of the module grade and an A4 Consultancy Project Proposal Digital Poster worth 20%. The proposal should provide an in-depth analysis of a selected business or management issue and establish a comprehensive research methodology for investigating the identified challenge. The assignment requires students to select an existing organisation and critically examine between one and three current and ongoing organisational challenges. The discussion should be evidence-based and supported by relevant, recent and credible sources, such as academic journals, company reports and other appropriate research. Students are encouraged to establish links between the selected challenges, current affairs, news events and the United Nations Sustainable Development Goals where relevant. The proposal must establish a clear research aim and three research objectives connected to the selected organisational challenges. Students must demonstrate awareness and application of appropriate research methodologies, including consideration of qualitative and quantitative approaches. The assessment also encourages the development of one or two concise research questions and requires students to demonstrate how the selected research methods can be applied to investigate the identified challenges. Students must also develop a feasible research plan and discuss ethical considerations, particularly those relating to secondary data collection. The digital poster should communicate the research plan clearly and demonstrate data analysis and data presentation skills through appropriate graphs, charts and tables. The final proposal should critically organise and synthesise information, provide a clear conclusion, and maintain professional academic standards. The recommended structure consists of a cover page, table of contents, list of abbreviations where appropriate, introduction, critical discussion of challenges, research aim and objectives, application of research methodologies, ethical considerations, research plan, critical organisation and synthesis of information, conclusion, references, the Consultancy Project Proposal Digital Poster and appendices where required. The main proposal has a 1,500-word limit, while the digital poster should not exceed one A4 page. The assignment requires Harvard referencing and the report should be written in the third person.
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Information Organization
3,000 words
Information Organization System Case Study
This assignment requires students to gain a practical understanding of an information organization system by selecting a system of their choice and systematically studying how it works, how it developed, and how it may evolve in the future. The selected system may include a library online catalog or library management system, database, search engine, or another appropriate information system. The assignment begins with identifying an information organization system and providing a link to the system or an information page about it. Students then research the history of the selected system and describe important milestones in its development. The research should address why the system was built, what existed before the system, who its intended users are, whether it was developed from scratch or based on existing technology, and which companies or individuals were involved in its creation. Students are also asked to consider whether the system is an appropriate fit for the organization. A major component of the case study is an examination of the fields and metadata within the system. Students identify the types of information objects entered into the system and examine at least four to six fields, such as author, title, publication year, patient name, date of visit, or reason for visit, depending on the selected system. The assignment also asks students to discuss whether the fields are appropriate for the system and its users and whether additional fields could be useful. The assignment further requires an examination of how the system can be evaluated and what its future may look like. Students consider current evaluation methods, user involvement, potential integration of emerging technologies such as artificial intelligence, possible replacement by more efficient systems, areas of concern, and the qualifications and experience required to manage the system. The final submission must be written as an essay describing the selected system. It should include a title page, an introduction, complete sentences and paragraphs, and a length of approximately 2,000–3,000 words. At least four APA-style references are required, with at least two references coming from assigned course readings.
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Multimodal Sentiment Intelligence Platform for Dynamic Market Insights
This assignment presents the development of a Multimodal Sentiment Intelligence Platform for Dynamic Market Insights. The project addresses the need for real-time market sentiment analysis by combining text and visual data through an AI-driven multimodal approach. Traditional sentiment analysis methods may have limitations when dealing with diverse data modalities, and this project aims to address this gap by integrating multiple artificial intelligence and deep learning techniques. The primary objective is to develop an AI-driven platform capable of performing real-time sentiment analysis and supporting market trend prediction. The proposed system also aims to generate business intelligence insights that can support applications in marketing, finance, and customer service. The project incorporates deep learning, large language models, and multimodal fusion techniques to improve sentiment understanding. For text-based sentiment analysis, the assignment identifies BERT and GPT-2 for sentiment classification. For visual sentiment analysis, YOLOv8 is used for object detection while DeepFace is incorporated for facial emotion recognition. Feature-level and decision-level fusion strategies are applied to combine information from different modalities and improve the overall sentiment analysis process. Retrieval-Augmented Generation (RAG) is also incorporated to provide context-aware sentiment insights. The proposed platform uses Amazon reviews and IMDb reviews as text datasets. For image or video-based multimodal data, the assignment references the CMU-MOSEI dataset and an Amazon-Reddit merged reviews dataset. Overall, the work focuses on combining natural language processing, computer vision, deep learning, large language models, multimodal fusion, and retrieval-augmented generation to create a platform capable of producing dynamic sentiment and market insights.
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Sustainable Development / Resource Management
6,000 words
Resource-Related Challenges in a Selected Country (STREAM) — Term Paper: India's Energy Sector, Coal Dependence and the Transition to Solar and Storage
This first-semester term paper for the STREAM programme takes a single country and a single resource sector and examines the challenges that arise where the two meet. India was selected for its energy sector — a case where scale, growth rate and an entrenched coal base make the tension between development need and environmental limit unusually sharp. The paper is written as an academic scientific text of roughly twenty pages, structured across the four sections the brief specifies and supported throughout by peer-reviewed literature, institutional reports and official statistical sources. The opening section establishes the country context: geographical position and climatic variation, population size and distribution, the shape and growth trajectory of the economy, development status against recognised indicators, and why the energy sector in particular is decisive for the country's near-term development path. The second section analyses the current status of the resource itself. Domestic coal reserves and their geographical concentration are set against renewable potential, particularly solar irradiance across the western and southern states. Production and consumption figures are traced over recent years, the import dependency for crude oil, gas and coking coal is quantified, and the major pressures are identified — demand growth outpacing capacity addition, the financial condition of distribution utilities, grid integration limits for variable generation, and the storage gap that constrains how far solar can displace baseload. The third section covers infrastructure and value chains. It describes the generation fleet, transmission and distribution network, and the logistics moving coal from pithead to plant, then follows the value chains attached to the resource — mining, power generation, equipment manufacturing and the growing domestic solar module and cell industry. Key stakeholders are mapped across central and state government, regulators, public and private generators, distribution companies, industrial consumers and the mining workforce whose livelihoods a transition directly affects. The final section addresses environmental problems and their connections to resource use. Ambient air quality and its public health burden, the water demand of thermal generation in already water-stressed basins, land degradation and displacement around mining regions, ash management and greenhouse gas emissions are each examined as consequences of the existing energy system rather than as separate issues. The section closes on future developments and risks: the plausible trajectories for renewable capacity and storage deployment, the stranded asset question for recently built thermal plants, and what a socially just transition would require of policy.
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Data Management / Business Analytics
2,500 words
Data and Decision Making (BS776) — Business Report: Two-Source Data Analysis in Python for Evidence-Based Decision-Making
This Level 7 report applies data management theory to a self-selected industry problem and carries it through to a working Python analysis and a defensible business recommendation. The brief is deliberately open on sector — finance, healthcare, transport, cyber security, business intelligence and others are all permitted — but firm on one point: the chosen topic must carry a genuine business implication rather than being a purely technical or clinical analysis. The work therefore begins by framing a specific data-driven decision the organisation needs to make, and returns to that decision at every stage. Two distinct data sources are then identified from approved open repositories and critically evaluated side by side. The evaluation covers the data types each holds, how the data was collected and what bias that introduces, how each is stored and managed, and where the weaknesses lie — proposing concrete data management solutions for the problems identified rather than simply cataloguing them. The analytical core examines, transforms and explores both datasets using univariate and multivariate techniques. All work is carried out in Python within Google Colab, with full screenshots of the code and outputs placed in the appendices and the live Colab link shared for verification. Charts and tables sit in the main body where they support interpretation, each labelled and referenced back to its data source, and each appendix is cited from the narrative so the reader can move between argument and evidence. Data cleaning and transformation steps are shown and justified, not glossed. Findings are reported at length and converted into a clear recommendation covering both the immediate decision and the current and future direction of data management for the business. The limitations section is written honestly — sample coverage, data recency, the assumptions the transformation forced, and what the proposed solution cannot address. Running alongside this, the module's weekly consolidation discussions are evidenced. Five or more critical responses across units two to nine are screenshotted, dated, individually labelled as appendices, and each supported by academic and practice references. Crucially, these are not left sitting in the appendix: they are cited and used within the main body to support the critical discussion, which is where the marks for that component sit. The report follows the prescribed structure — title page, executive summary, contents, introduction, main section with subsections per task, findings, recommendations, limitations, conclusion, Harvard reference list and full appendices — submitted as a single file.
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Data Management / Business Analytics
2,500 words
Data Design Management (BS514) — Data Strategy Consultancy: Relational Database Design, SQL Implementation and Pipeline Transformation
This Level 7 assessment places the writer in the role of a Data Strategy and Analytics Consultant appointed by an organisation operating in a realistic industry sector. The brief is entirely simulated, so the work sets out a defensible set of assumptions about the organisation's data environment before any design begins, and populates the resulting database with synthetic but realistic records. The deliverable is a slide deck carrying full explanatory notes, submitted as a single PDF, and weighted across three connected tasks. Task one establishes the business case. It describes how the chosen organisation currently collects, stores and uses data across customer interactions, sales transactions, operational processes and digital channels, and identifies where that fragmented picture costs the business in efficiency, resource use, retention and decision quality. A SWOT analysis benchmarks the organisation against a named real-world competitor in the same sector, drawing on publicly available market information rather than assertion. The section closes with a critical evaluation of modern relational database advancements — cloud-hosted SQL services, distributed architectures and data warehousing — assessed not in the abstract but against what each would actually change about this organisation's business model. Task two carries the heaviest weighting and is the technical core. Key business entities are identified from the scenario, a current-state data flow diagram traces how data moves from collection points through to storage and reporting with the existing ETL approach made explicit, and a future-state ER diagram is then built with full attributes, primary and foreign keys, relationships and cardinality. The design is normalised to third normal form with the decomposition reasoning shown. Implementation follows in SQL: tables created with appropriate integrity constraints, at least ten realistic sample records inserted per table, and five business questions answered through working queries — highest-performing product or campaign, average conversion by category, workload distribution across staff, accounts with overdue or pending items, and most effective service channel. Outputs accompany every script. A transformation demonstrating query optimisation is included with before-and-after samples so the improvement is evidenced rather than claimed. Task three steps back to the technology decision. Two widely used data processing platforms are compared in tabular form across integration, cleaning, transformation and automation capability, judged specifically against this organisation's constraints, with a reasoned justification for the tool finally selected. The transformed dataset is then used to answer two management-level questions — where investment should be prioritised and how retention might be improved from observed behavioural patterns — each interpreted briefly and tied back to a concrete recommendation. Slide structure follows the prescribed layout, SQL scripts sit in the notes section, and the complete script file is reproduced in the appendix.
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Business Strategy / Digital Business and Innovation
3,125 words
Safaricom Business Hub: Strategic B2B Digital Payment Platform for East African SMEs
This strategic business case proposes the Safaricom Business Hub, an integrated B2B digital-payment platform designed to support small and medium-sized enterprises across East Africa. The proposed solution responds to Safaricom’s need for digital diversification as traditional voice revenues mature, while leveraging the growth of M-Pesa and the wider transition toward digital financial services. The platform combines invoicing, bulk payments, cash-flow analytics and integrations with accounting systems such as Xero, QuickBooks and SAP. The report begins by analysing Safaricom’s current strategic position, including subscriber growth, revenue performance, declining voice services, M-Pesa transaction growth and market saturation. It then assesses the wider East African B2B digital-payment opportunity, considering market size, digital adoption, the SME population, regulatory developments, smartphone penetration and operational inefficiencies associated with manual invoicing and reconciliation. Competitive analysis evaluates Safaricom against established banking solutions, international fintech providers and specialist payment gateways. The strategic case identifies several potential advantages associated with Safaricom’s existing M-Pesa infrastructure, agent network, brand position and payment-services capabilities. The proposed Business Hub addresses fragmented SME financial processes through automated invoicing, bulk payment processing, real-time cash-flow analytics and integration with existing accounting platforms. The business plan also provides a four-phase implementation roadmap, covering MVP development, pilot testing, Kenyan market launch, regional expansion and ecosystem development. Financial projections consider customer growth, revenue, EBITDA, customer acquisition cost, lifetime value, payback and return on investment, alongside sensitivity scenarios for different levels of market adoption. Finally, the report evaluates competitive, regulatory and market-adoption risks and links the proposed investment to Safaricom’s broader strategic diversification objectives. Overall, the work integrates strategic analysis, fintech innovation, market opportunity assessment, implementation planning, financial modelling and risk evaluation to present a commercial case for expanding Safaricom’s digital financial-services ecosystem. Overview word count: approximately 340 words. One useful note for the public Reference Library: I would upload the clean original assignment/business plan rather than the AI-detection or similarity-report versions if you have it, because these two PDFs contain checker-report pages in addition to the coursework itself.
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Computing and Digital Technologies
3,000 words
Contemporary Computing and Digital Technologies: AI Agents Hackathon Reflective Report
This postgraduate reflective assessment forms part of the Contemporary Computing and Digital Technologies module and is based on experiential learning undertaken through an AI-focused hackathon. The hackathon theme, “AI Agents Unleashed – Building the Future of Automation,” requires MSc students from computing-related disciplines to collaborate on intelligent agent-based solutions capable of automating complex tasks, solving real-world problems and supporting human decision-making. The hackathon encourages students to investigate agent-based system design, intelligent automation and responsible AI development. Potential applications include autonomous cybersecurity monitoring, multi-agent systems for information gathering and decision support, automated data pipelines, intelligent software-development assistants, and conversational systems such as virtual tutors or career coaches. Students may use code-based approaches or platforms such as Flowise, Microsoft Power Automate and Make.com, while more advanced implementations can use technologies including LangChain, AutoGen, Python-based agent SDKs, APIs and large language models. The 3,000-word Individual Reflective Report, worth 70% of the module assessment, evaluates the student's learning and professional development arising from these experiential activities. The first component is a 2,000-word Portfolio of Evidence, requiring evidence-based reflection on participation in the hackathon. Students should evaluate their leadership and teamwork competencies using concrete evidence such as screenshots, code commits and feedback while identifying key lessons for personal and professional development. They must also consider how the experience applies to future research, career development or professional practice. The remaining 1,000 words comprise a Critical Self-Reflection examining the student's personal contribution and achievement of learning-contract goals. Students are expected to critically consider challenges encountered, how those challenges were addressed, lessons learned and their development as effective collaborative team members. Overall, the assessment integrates technical experimentation, reflective practice, teamwork, leadership, professional development and responsible use of emerging AI technologies, supported by a structured portfolio of evidence
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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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Machine Learning / Artificial Intelligence and Data Science
1,011 words
End-to-End Machine Learning Model Development, Testing and Evaluation
This Level 7 Machine Learning and Intelligent Agents assignment requires students to develop and document an end-to-end machine-learning solution, covering the complete process from data preparation through model training, tuning, testing and evaluation. Students independently select a suitable dataset or scenario, formulate an appropriate research question and determine whether the problem should be addressed using supervised learning, unsupervised learning or reinforcement learning. Appropriate machine-learning algorithms must then be implemented to create a model capable of being trained and objectively tested. The assessment encourages the use of a structured machine-learning development methodology. Students are expected to explain the selected scenario and data source, perform suitable data preparation and Exploratory Data Analysis (EDA), and provide a reasoned justification for the machine-learning methods selected. The development process should demonstrate how the chosen algorithms are trained and fine-tuned before their performance is evaluated using established and relevant metrics. Published academic research should be incorporated to justify methodological choices and support the interpretation of results. The technical work is normally documented within a Jupyter Notebook, combining Markdown explanations with executable code cells. Alternatively, the report may be produced in Microsoft Word provided that the Python implementation is included. The assignment therefore assesses both conceptual understanding and practical programming competence. Students must demonstrate an ability to identify the performance of machine-learning algorithms, implement machine-learning techniques using an object-oriented programming language, and evaluate which algorithms are appropriate for a particular analytical brief. Assessment places particular emphasis on three areas: the Introduction, the Machine Learning Process, and the Evaluation of Model Performance. The marking criteria reward strong understanding of machine-learning concepts, a functioning and thoroughly tested implementation, appropriate selection of algorithms, and critical evaluation of the final solution. At the highest achievement level, implementations are expected to work without exception, satisfy the required functionality, demonstrate comprehensive testing and extend beyond the basic requirements. Overall, the assignment combines research-question formulation, data analysis, algorithm selection, machine-learning implementation, model optimisation and evidence-based evaluation within a reproducible technical workflow. All academic sources and supporting material must be presented using Harvard referencing.
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Management / Business Management
5,000 words
Principles of Management: AstraZeneca Management Analysis and Skills Development Report
This Masters-level Principles of Management assignment examines the management practices, organisational environment and managerial functions of AstraZeneca plc. The assessment is structured as a 5,000-word management report in which the student acts as a business consultant and critically evaluates how management theories, concepts and practices contribute to organisational performance and value creation. The work requires the application of relevant academic literature alongside case-study evidence and independent research on AstraZeneca. The first part of the assessment considers key management theories and practices. Students are expected to examine how management contributes to AstraZeneca's success, apply an appropriate dimension of the Competing Values Framework, and select an additional relevant management theory. Suggested theoretical perspectives include Scientific Management, Bureaucratic Theory, Administrative Theory, Contingency Theory and Total Quality Management, although students are encouraged to select theories most appropriate to the organisation rather than applying every available model. The assignment also evaluates AstraZeneca within the global business environment. Frameworks such as LoNG-PEST or Porter's Five Forces may be used to analyse global, national and local influences, including significant opportunities and threats. Students then critically analyse an internal organisational challenge and consider how the core management functions of planning, organising, leading and controlling can be applied to address it. Supporting analytical approaches may include Value Chain analysis, VRIO and stakeholder analysis. A further component focuses on personal and professional development. Students complete a Personal SWOT analysis and construct a Skills Development Plan linked to future career aims. This is followed by a 500-word reflective statement examining personal management competencies, including self-management, problem-solving and decision-making. An appropriate reflective framework, such as Borton, Kolb or GROW, is applied to structure the reflection. Overall, the assessment integrates management theory, organisational analysis, global business considerations, managerial decision-making and reflective professional development. It is designed to demonstrate Level 7 critical analysis and the practical application of management concepts to a contemporary multinational organisation. The wider module covers management theories, stakeholder management, global management, planning and decision-making, human resource management, leadership, operations and finance for managers
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People Analytics / Human Resource Management
2,003 words
Principles of People Analytics and Evidence-Based Decision Making
This CIPD Level 3 assessment introduces the principles of people analytics and evidence-based decision making within the people profession. It focuses on how data, professional expertise, research evidence and stakeholder information can be used to diagnose organisational issues, support rational decision making and improve people practices. The unit emphasises the practical application of analytics rather than data collection alone. The assessment uses a recruitment scenario in which the learner applies for the position of People Analytics Administrator at Company X, an organisation providing HR and people-management solutions. Learners complete an assessment pack containing eight questions designed to demonstrate understanding of how analytics can support business and people decisions. The written component requires learners to explain evidence-based practice and demonstrate how it could be applied in an organisational context. Other areas include the importance of accurate data in diagnosing problems, different forms of data measurement, the role of organisational policies and procedures in decision making, and how people professionals create value for employees, organisations and wider stakeholders. Learners must also consider how a people analytics professional can remain customer focused and standards driven. The practical analytics element uses employee overtime data from Blue Mountain Patisserie. Learners calculate average overtime for individual employees, express overtime as a percentage of normal working hours, interpret patterns within the data and identify potential organisational problems and possible solutions. Findings must then be communicated using at least two different diagrammatic formats, such as bar graphs, pie charts or line graphs. The required written evidence is approximately 1,500 words for Questions 1–6 and 500 words for Question 7, giving approximately 2,000 words in total, with the visualisations excluded from the word count.
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Computer Science / Database Systems
4,000 words
Advanced Databases (KL7011) — NORTHERNTOURS Coach Travel Database: EER Design, Oracle Implementation, Object-Relational and NoSQL Extensions
This piece of work addresses a four-part Masters-level assessment in Advanced Databases built around NORTHERNTOURS, a fictitious coach travel operator running services across cities, towns and tourist sites in the North East of England. The company sells tickets through a network of independent travel agents, each currently working from a paper-based sales book, while NORTHERNTOURS itself maintains separate paper records for routes, schedules, seat availability, vehicles and drivers. The brief asks for a single computer-based system capable of replacing both, tracking every agent transaction while giving the company control over ticket issue and seat allocation. Part one covers the conceptual and logical design. An enhanced entity-relationship model was produced covering agents, agent employees, customers, tickets, routes, stops, schedules, vehicles, drivers and the meal provision recorded at each stop, with key attributes, primary keys and full structural constraints shown. Because the scenario does not name identifiers for most entity types, appropriate surrogate and natural keys were devised and justified. The diagram was then mapped to a logical relational schema, normalised to third normal form, with a documented naming convention applied consistently across relations, attributes and keys, and every element recorded in a text-based data dictionary giving names, data types, descriptions and constraints. Part two moves to implementation in Oracle. A full DDL script creates the relations with primary and foreign keys and a substantial set of check constraints — key format patterns, positive seat counts and fare values, date ordering on schedules. Sample data populates the relevant tables, and two retrieval problems are answered twice over, once in relational algebra and once in SQL: schedules between Newcastle and Berwick-upon-Tweed with seven or more seats free in the coming fortnight, and the agent with the highest ticket sales across a defined month. Spooled session output evidences each script running. Part three revisits the conceptual design to argue where object-relational features earn their place — nested route-and-stop structures and composite address and contact types being the clearest candidates — implemented using Oracle object types, VARRAYs and nested tables, and demonstrated through two multi-join aggregate queries. A parallel discussion identifies the schedule and availability workload as a fit for document-oriented NoSQL storage, with representative code and a reasoned account of the denormalisation trade-offs involved. Part four is a report to the managing director covering sustainability, professional, legal, ethical and security obligations, alongside diversity, inclusion, cultural and environmental matters, commercial risk evaluation and mitigation, supported throughout by current literature and published standards.
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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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Operations and Supply Chain Management
1,800 words
Strategic Sourcing and Supply Chain Resilience Under Global Uncertainty — A Firm-Level Critical Evaluation
This type of postgraduate coursework asks students to take a single real firm — a British company, or a multinational with substantial UK operations — and critically evaluate how its sourcing and supply chain strategy has adapted to a decade of sustained disruption: the pandemic, geopolitical conflict, tariff volatility, and departure from the European single market. The analytical scope is broad but the depth expectation is narrow. Students choose one or two themes rather than surveying all of them: insourcing versus outsourcing and location decisions; single versus multi-sourcing across supplier segments or regions; how supplier selection and monitoring criteria have shifted toward reliability and geographic proximity; alignment between sourcing decisions and wider corporate objectives; supplier and customer relationship management under cross-border friction; inventory tactics such as stockpiling and safety stock repositioning; digital adoption for visibility and compliance; sustainable sourcing under cost pressure; or risk management around currency, customs and compliance. The evidence base is deliberately mixed. Alongside academic literature, students are expected to draw on annual reports, shareholder briefings, company statements, practitioner journals and recent news coverage — with a minimum spread of credible sources across both categories, and some of the non-academic material drawn from the most recent year so the analysis reflects current firm behaviour rather than historical commentary. At least one theoretical framework from the module or the wider literature must be applied to the firm's decisions, and at least one recent documented practice must be examined with specific sourcing. Two requirements distinguish strong submissions. The first is criticality: the brief explicitly separates evaluation from description, and marks weight critical analysis most heavily. Reporting what a firm did is not the task; assessing whether it was the right response, and what opportunities and risks it created, is. The second is the recommendation — at least one specific, actionable proposal with steps, anticipated obstacles, expected outcomes, and a clear line back to the firm's own stated goals. A generic suggestion to "diversify suppliers" fails this test; a costed, sequenced proposal grounded in the firm's actual constraints does not. Word-count conventions are stricter than students often expect: in-text references, tables, illustrations and front matter typically count, while appendices and the reference list do not. Our support on assessments of this type is guidance-based. Typical areas of help include: narrowing a firm and theme so the analysis fits the word limit, explaining the difference between description and critical evaluation with worked examples, clarifying how a theoretical framework should structure an argument rather than sit decoratively in a paragraph, checking source mix and Harvard referencing consistency, and reviewing a completed draft against the published assessment weightings.
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Assignment 2 - Individual project Image segmentation
Assignment tasks This assignment will focus on Image Segmentation using the ADE20K dataset. This is an individual assignment where each student will produce a report on the data analysis they will perform. You are encouraged to utilise Google Colab for the coding part of your assignment. https://herts.instructure.com/courses/129101/assignments/406384 1/86/17/26, 12:10 PM Assignment 2 - Individual project - Image segmentation - 25% You will explain and discuss the data processing, the method(s) you make use of and elaborate the outcome. You will work on the ADE20K dataset (explained below in more detail) to research viable models to train, discuss different approaches to explore and visualise the data (i.e., perform EDA), build a tool to pre-process the dataset, and customise your chosen model(s) to improve performance. You will produce a code that does semantic segmentation of the 4 classes targeted in this assignment: person, car, book, airplane. In more detail, your model(s) should identify which of these 4 classes the region of the image corresponds to, and should be applicable to any unlabelled image. To be clear: doing only binary segmentation (i.e. any class vs background) will result in a very large penalty, as you will be considered not to have done the required task. You may use more than one model, but one has to be trained partially or fully by you. Should you use more than one, you are encouraged to compare your main trained model with one or more pre-trained models.
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