Academic Model Answers Library — Megaminds (UK Postgraduate)

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International Human Resource Management 800 words

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

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

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Computing Science

Writing a Literature Review in Computing Science

This individual assessment requires students to write a concise literature review on a selected topic within computing science. The review should be no more than six pages in length and should be written in a style appropriate for a general computing science audience. The assignment is designed to demonstrate technical knowledge, independent learning, effective written communication and professionalism in producing a concise technical document. Students must select a research topic from one of five permitted areas: algorithmic bias and fairness, a data science application, quantum computing, the Internet of Things (IoT), or the use of artificial intelligence in cybersecurity. Possible topics include how algorithms can discriminate and techniques for detecting and correcting algorithmic bias, applications of data science in areas such as agriculture or healthcare, quantum computing algorithms and hardware, technical IoT problems and potential solutions, and the use of AI for cybersecurity threat detection and prevention. The literature review must contain several required components. The first page should contain only the title, student number, abstract and statement of AI usage. The abstract must provide a concise overview of the review and must not exceed 200 words. The report should also include an introduction that provides broad background information before narrowing the discussion to the selected research topic. The introduction should explain why the topic is important and provide relevant context and examples of applications. Students are expected to review a range of relevant literature, including theories, methods, techniques, ethical concerns or tools where appropriate. The selected literature should not simply be described individually; instead, students must synthesise the sources to identify important themes, findings and areas of interest and provide a critical review of the literature. The conclusion should summarise the main findings, identify open issues and discuss possible future directions. The assessment must include a bibliography with accurate and up-to-date references formatted using Harvard style. The final document may be prepared in LaTeX or Word but must use one of the provided templates and be submitted as a PDF through Blackboard. The complete review, including figures and bibliography, must not exceed six pages. The assessment is marked according to structure, sources and their description, synthesis and critical review, and presentation.

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Digital Marketing / Web Design and User Experience 800 words

Digital Marketing Portfolio Website: User Experience, SEO and Professional Digital Branding

This digital marketing assessment requires students to create and launch a fully functional personal portfolio website designed to showcase their professional capabilities, creativity and readiness for employment or client-facing work. The website operates as a digital business card and professional showcase, demonstrating the application of digital marketing strategy, user-centred design, storytelling, usability and digital content creation. Digital Portfolio Website The website must contain a homepage, contact page and portfolio or projects section. The homepage introduces the student and provides an engaging overview of the portfolio, while the contact page includes appropriate professional communication channels such as email or LinkedIn. The projects section must feature approximately three to five digital marketing work samples, which may include mock-ups, content or other digital artefacts. The overall site should demonstrate effective structure, aesthetics, usability and intuitive navigation. Digital Portfolio Website Students must also complete a prescribed LinkedIn Learning course on Wix or WordPress and submit the associated completion certificate. This supports the practical website-development component and demonstrates engagement with contemporary digital-design tools and platforms. Digital Portfolio Website A major component is the reflective rationale, which may be submitted as an 800-word written piece or a four-to-six-minute video commentary. It explains and justifies the design decisions made, the SEO strategies implemented and changes introduced to enhance the user experience. The rationale must be supported by credible sources and demonstrate alignment between theoretical principles and practical design choices. Digital Portfolio Website SEO is explicitly assessed through the effective use of metadata, keywords and image alt text, while design performance also considers originality, calls to action, responsive behaviour, mobile usability and effective use of Wix or WordPress features. The marking structure allocates 20% to website structure and usability, 15% to design and creativity, 15% to SEO, 40% to the reflective rationale, and 10% collectively to the LinkedIn Learning certificate and cover page. Digital Portfolio Website Digital Portfolio Website Overall, the assessment integrates digital marketing, personal branding, web design, UX, SEO, content creation and reflective professional practice. Overview word count: approximately 345 words. AI-use note: this assessment is under Category 1 – Authorised use of AI. AI may be used within platforms such as Wix or WordPress to help create the portfolio, but AI must not be used to write the reflective rationale, which must be composed entirely by the student. Digital Portfolio Website

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

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

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Marketing / Consumer Marketing 1,987 words

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

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

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Digital Marketing / Marketing Analytics / Data-Driven Marketin

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

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

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Entrepreneurship / Leadership and Management 3,500 words

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

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

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Strategic Management / Sustainability / Responsible Leadership 2,500 words

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

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

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International Human Resource Management / International Business 800 words

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

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

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Data Science / Time Series Analysis / Machine Learning

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

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

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Supply Chain Operations and Logistics Management 3,000 words

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

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

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Computer Science / Parallel Computing

Parallel Merge Sort with Load Balancing

This technical research article investigates the performance limitations of conventional parallel merge sort and proposes a load-balanced alternative designed to improve processor utilisation in distributed-memory parallel computing systems. Traditional parallel merge sort progressively reduces the number of active processors during successive merge stages, causing many processors to remain idle and reducing the performance benefits of parallelisation. The proposed approach addresses this limitation by ensuring that all processors continue participating throughout the merging process. Parallel_Merge_Sort_with_Load_B… The paper first explains the conventional parallel merge-sort process, in which data are locally sorted before processors are paired for a series of merging operations. At every subsequent stage, the number of participating processors is halved until only one processor remains responsible for the final merged list. This results in poor processor utilisation and increasing workload concentration. Parallel_Merge_Sort_with_Load_B… The proposed load-balanced parallel merge sort distributes each partially sorted list across multiple processors so that every processor maintains approximately the same number of keys throughout execution. Processor groups use histograms and boundary values to determine how data should be redistributed during merging. Histogram-based partitioning reduces unnecessary data movement, while an index-swapping mechanism is introduced to avoid transferring large blocks of keys when logical processor reassignment can achieve the same result more efficiently. Parallel_Merge_Sort_with_Load_B… Parallel_Merge_Sort_with_Load_B… The algorithm was implemented in C using MPI and experimentally evaluated on a Cray T3E parallel computer and an eight-node PC cluster. Testing considered both uniform and Gaussian key distributions. Results show that performance improvements increase as processor count grows, although communication and histogram-management overhead can reduce benefits for small workloads. Parallel_Merge_Sort_with_Load_B… The proposed technique achieved a maximum merge-phase speedup of 9.6 on a 32-processor Cray T3E and 2.3 on an eight-node PC cluster when processing four million keys. The study concludes that distributing approximately equal workloads across processors can substantially improve parallel merge performance and may also be applicable to related parallel sorting algorithms. Parallel_Merge_Sort_with_Load_B… Overview word count: approximately 330 words. For your portal, I would not label this as university coursework unless you also have the actual assessment brief that uses this paper. This PDF itself only establishes a published academic paper and the authors’ Korea University affiliation.

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Artificial Intelligence / International Business 3,000 words

AI Innovation Consultancy: Evaluating Artificial Intelligence Solutions for Business Problems

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

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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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Computer Science / Research Methods / Specialist Research 2,800 words

Research Specialism Report: Critical Review of Open Research Questions in Computer Science

This Advanced Research Topics in Computer Science assessment requires students to critically examine a research paper associated with their chosen MSc specialism and demonstrate an understanding of how established research techniques are used to create and extend knowledge in computer science. Eligible specialisms include Artificial Intelligence, Networking, Cyber Security, Software Engineering and Data Science. The assessment is intended to prepare students for deeper independent research as part of their Master's project. 7COM1084+Research+specialism+re… Students begin by providing a clear introduction to their selected research specialism and explaining the broader research area in a way that is accessible to readers with general computer-science knowledge. The report then identifies the open research question presented in the relevant 7COM1084 specialist lecture paper, explains the problem in detail and evaluates why it is scientifically significant or relevant to a real-world application. 7COM1084+Research+specialism+re… A substantial literature-review section requires students to examine existing and related research beyond the specialist lecture paper. The aim is to identify what previous work has achieved, explain why existing approaches do not fully solve the research problem and identify further unresolved questions. 7COM1084+Research+specialism+re… The research-methods section focuses on the approaches used in the selected specialist paper. Students are expected to describe and critically evaluate those methods, considering both their strengths and limitations. They must then propose an alternative or extended research approach that could build on the published work and investigate related open problems, drawing on principles of experimental design and theoretical or practical research. 7COM1084+Research+specialism+re… The final reflective component asks students to explain their personal investment in the research area, including why the selected question interests them and how their own strengths and prior experience would support future research in that domain. 7COM1084+Research+specialism+re… The report must not exceed 2,800 words ±10%, must use the Harvard referencing system, and must include at least 20 references, one of which must be the relevant 7COM1084 specialist paper. 7COM1084+Research+specialism+re… 7COM1084+Research+specialism+re… 7COM1084+Research+specialism+re… Overall, the assessment integrates research specialism knowledge, literature review, open-problem identification, methodological critique, research design, future-work development and scholarly communication within a Level 7 computer-science research context.

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Data Science / Artificial Intelligence / Generative Modelling

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

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

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

Professional Project Portfolio and Strategic Business Presentation

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

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Cyber Security / Penetration Testing

Web Application Penetration Testing and Security Vulnerability Assessment Portfolio

This postgraduate cyber security portfolio requires students to conduct a structured penetration test of a controlled web application and document the technical findings in a professional security-testing format. The assessment develops practical competence in identifying, validating and communicating security vulnerabilities while maintaining appropriate legal, ethical and professional boundaries. Assessment Brief CMP-L021 (PG) … Students begin by performing network and service enumeration, identifying open ports and the services running on the target host. They are expected to interpret the security implications of the findings and provide appropriate recommendations to a hypothetical client. The assessment then progresses into web-application vulnerability testing using tools such as a web browser, Burp Suite Community, Nmap and student-developed scripts. Assessment Brief CMP-L021 (PG) … A major part of the portfolio examines common web-security weaknesses including SQL Injection and Cross-Site Scripting. Students must demonstrate how they tested the application, capture relevant requests and responses, and explain the evidence supporting their conclusions. Additional tasks involve application and server reconnaissance, including identification of technologies, server versions, publicly exposed files and other information that may create security risks. Assessment Brief CMP-L021 (PG) … The higher-level reporting component requires students to document significant vulnerabilities using the conventions of a professional penetration-test report. This includes assigning CVSS scores, relating identified weaknesses to the OWASP Top 10 and NIST classifications, and supporting findings with appropriate technical evidence. Assessment Brief CMP-L021 (PG) … Students must also produce an executive summary for a non-technical audience, considering security, privacy, regulatory exposure and budget implications. A vulnerability table linking technical weaknesses with relevant regulatory concerns is also required. Overall, the assessment integrates technical penetration testing with risk communication, vulnerability classification, evidence collection and professional security reporting. Assessment Brief CMP-L021 (PG) … Overview word count: approximately 320 words. AI-use note: AI can be used in this assessment, but any use must be acknowledged and AI-generated outputs must be appropriately cited. Assessment Brief CMP-L021 (PG) …

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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 Mining / Data Science

Customer Service Escalation Risk Analytics Using Data Mining and Machine Learning

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

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

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

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

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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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Engineering and Environment Advanced Practice 3,000 words

AP Research Project – Reflective Individual Report and Poster Presentation

This assessment is the Advanced Practice (AP) Research Project for the Engineering and Environment Advanced Practice London Campus Research Project module. It is designed for postgraduate students undertaking an independent research project with supervisory guidance. The assessment provides an opportunity to reflect critically on the research process, knowledge gained, professional development and challenges encountered during the project. Students are expected to demonstrate independent learning, research skills, critical thinking and the ability to communicate complex ideas in a professional context. The main assessment is a 3,000-word Reflective Individual Report, which contributes 80% of the module assessment. The report is structured around four key areas. The first section, Finding a Research Topic, requires students to explain how and why they selected their research topic, the research tools and search strategies used, the library collections explored, their research aims and objectives, and relevant discussions or recommendations received from their supervisor. The second section, Professional Activities, focuses on reflection on research development activities, scheduling, the independent researcher role, challenges such as time management, and communication with the supervisor. The third section, Literature Review and Research Work, requires students to critically review relevant literature, discuss their research method, demonstrate major research activities and consider the feasibility of the selected method, including challenges and recommendations. The final section, Reflection of Research Project, requires critical reflection on personal strengths and weaknesses, continuous self-development and the relevance of research activities to the student's programme of study and future career. Areas such as decision making, problem solving, communication and influencing, technical skills, collaboration, innovation and proactivity should be considered. The second component is a 10-minute Poster Presentation worth 20% of the assessment. The poster should provide a balanced combination of visuals and text and present the research objectives and significance, a summary of the literature review and research method, key research findings, and conclusions and recommendations. The assessment also requires appropriate academic presentation, including a cover page, table of contents, page numbers, figure and table captions, numbered headings and consistent formatting. Harvard or APA referencing may be used. The report is submitted through Turnitin and is subject to anonymous marking. The assessment is a Pass/Fail module, with students required to achieve at least 50% to pass.

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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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Digital Marketing

Three Weekly Digital Marketing Tutorial Challenges

This assessment consists of three weekly digital marketing tutorial challenges designed to develop practical skills in digital marketing, consumer insights, content creation, inclusive communication, ethical storytelling and campaign design. The assessment accounts for 45% of the module and requires students to apply digital marketing theory and consumer insight techniques in real-world marketing contexts. The activities are completed through tutorial-based learning, where students participate in discussions, receive tutor guidance and develop their work before submitting it through Canvas. The assessment focuses on applying consumer insights, data analytics tools and digital marketing strategies to create meaningful and responsible customer experiences. Challenge 1, titled “Are You Being Inclusive?” – Brand Audit & Persona for Ethical Reach, focuses on ethical digital auditing and inclusive persona design. Students select a brand from their home country and evaluate the inclusiveness and accessibility of its digital marketing across its website, social media and paid advertising. They then develop two to three detailed customer personas representing underserved or marginalised customer groups. Students also use AI analytics tools such as Google Trends, SparkToro or simulated AI insights to identify audience behaviours and preferences. The challenge is linked to SDG 10 – Reduced Inequalities and includes consideration of the ethics of using AI in digital marketing and its effect on the credibility of consumer insights. Challenge 2, titled “Don't Just Capture Attention – Respect It” – Campaign Idea Pitch, focuses on sustainable branding and growth. Students research the client's existing branding, examine opportunities to expand or sustain its audience and use consumer insight tools such as Google Trends, reviews and surveys to understand public perceptions. Students then create a visual mini-campaign promoting sustainable and transparent brand messaging, including social media content and AI-generated visuals. The campaign is connected to SDG 16 – Peace, Justice and Strong Institutions. Challenge 3, titled “Create, Educate, Disseminate & Evaluate”, develops digital social marketing and consumer engagement. Students extend the campaign developed in Challenge 2 into an interactive digital event that promotes positive behavioural change and educates audiences about a social issue. The activity must consider audience interests, increase interactivity and engagement, and provide evidence of positive engagement. This challenge is linked to SDG 4 – Quality Education. Overall, the assessment develops students' ability to combine digital marketing strategy, consumer insights, ethical considerations, sustainability and creative campaign design in practical marketing activities.

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Engineering and Environment Advanced Practice London Campus Research Project 3,000 words

LD7152 – AP Research Project

The LD7152 AP Research Project is a postgraduate research and reflective assessment for students studying within the MSc Computing Framework or MSc International Project Management programme. The module focuses on developing students as independent researchers and requires them to reflect critically on their research strategy, activities, learning and personal development. The assessment is designed to encourage students to recognise their achievements, identify challenges encountered during the research process and evaluate how their research experience has contributed to their academic and professional development. The assessment consists of two components: a 3,000-word Reflective Individual Report worth 80% and a 10-minute Poster Presentation worth 20%. Students are expected to work independently while receiving supervisory guidance. The reflective report requires students to demonstrate critical engagement with knowledge discovery and reflect on their educational development in relation to the challenges experienced during their research project. The report is structured around four main areas. The first section, Finding a Research Topic, is approximately 500 words and requires students to explain their chosen topic, why it was selected, the research tools and search techniques used, the Library collections explored, the research aims and objectives, and relevant discussions or recommendations from their supervisor. The second section, Professional Activities, is approximately 500 words and focuses on research development tasks, scheduling, the independent researcher role, challenges such as time management, and communication with the supervisor. The third section, Literature Review and Research Work, is approximately 1,500 words. It requires a critical review of relevant literature with appropriate citation, discussion of the research method and major research activities, and consideration of the feasibility, challenges and recommendations associated with the selected method. The fourth section, Reflection of Research Project, is approximately 500 words and focuses on achievements, contributions, strengths and weaknesses, continuous self-development and employability. Students are expected to reflect on areas including decision making, problem solving, communication and influencing, technical skills, collaboration, innovation and proactivity. The second assessment component is a 10-minute poster presentation. The poster should provide an overview of the research activities and communicate what the student learned during the research process. It should balance visual and textual information and include the research objectives and significance, a summary of the literature review and research method, key research findings, and conclusions and recommendations. The report must include a cover page, table of contents, page numbers and captions for figures and tables. The required formatting includes Times New Roman, 12-point font, numbered headings and approximately 1.2–1.3 line spacing. The assessment brief permits Harvard or APA referencing. The report is submitted electronically through Turnitin on Blackboard. The module is assessed on a Pass/Fail basis, with students required to achieve 50% or above to pass. The assessment also evaluates critical reflection, application of knowledge, independent learning, communication of complex ideas, personal development and reflection on technical leadership.

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Networking and Security Practice

Networking and Security Practice – Recorded Demonstration

This assessment for the MSc Cyber Security module Networking and Security Practice is a practical recorded-demonstration coursework designed to assess students' ability to configure, secure, troubleshoot and monitor a virtualised sandbox network. The assessment contributes 60% of the module mark and consists of four recorded demonstration videos, with each video limited to a maximum of five minutes. The completed videos are submitted through a Moodle quiz as video files or accessible links. The practical environment uses virtual machines running Ubuntu Server and Ubuntu Desktop on VirtualBox or UTM. Students deploy a four-machine architecture consisting of a Gateway, Webserver, Workstation and Zabbix-Server. The Gateway acts as the router, firewall and NAT gateway; the Webserver hosts an Nginx web server; the Workstation is used for administration and testing; and the Zabbix-Server provides network monitoring. The architecture requires appropriate network interfaces, IP addresses, routing and communication between the different internal networks. The coursework develops practical networking and system administration skills through several phases. Students install and configure operating systems, allocate virtual machine resources, configure static IP addresses, enable IP forwarding and NAT masquerading, and implement firewall rules using iptables. They also develop command-line proficiency using networking, DNS, security, remote-access and web tools including ping, traceroute, ss, nslookup, dig, nmap, Wireshark, netcat, SSH, SCP, rsync, curl and wget. Students must also configure secure remote access and deploy an Nginx web server. SSH must be hardened by disabling password authentication and root login, while key-based authentication is used for secure access. The Webserver must contain a customised landing page showing the student's name and student ID, which is accessed from the Workstation. The monitoring component requires installation and configuration of Zabbix, deployment of agents across the virtual machines, host monitoring, a customised dashboard containing at least five live-data widgets and configured alerts or triggers. Students must explain what their selected monitoring elements measure and why they are operationally useful. The traffic-analysis component uses Wireshark to capture and examine HTTP, ICMP and DNS traffic. Students apply appropriate filters, identify protocols using the Protocol Hierarchy and discuss the security implications of unencrypted HTTP traffic, including secure alternatives such as HTTPS and DNS over TLS. The security-evaluation component uses Nmap within the isolated virtualised sandbox to identify open ports and services, assess vulnerabilities and recommend mitigations. Students must also demonstrate iptables forwarding and NAT masquerading rules. The four videos cover Network Infrastructure, Network Monitoring, Traffic Analysis and Security Evaluation. The assessment is marked out of 100, with 35 marks allocated to Network Infrastructure, 25 to Network Monitoring, 20 to Traffic Analysis and 20 to Security Evaluation. Students are expected to provide clear voice narration, explain commands and outputs, demonstrate technical understanding and critically relate their work to network security. The assessment develops employability skills in Linux administration, remote system management, network troubleshooting, security hardening, packet analysis, port and service scanning, virtualisation and network monitoring. It also requires students to conduct security testing ethically within their own isolated virtualised environment and prohibits unauthorised scanning of university networks, public websites or other systems.

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Principles of Data Science 3,000 words

Principles of Data Science – Predictive Modelling and Data Analysis

This individual assessment for the Principles of Data Science module requires students to select, apply and critically evaluate data science methods, tools and techniques using one of three provided datasets and its associated scenario. The main assessment takes the form of a 3,000-word report in which students explore their chosen dataset, identify an appropriate predictive modelling approach, build and evaluate models, interpret the findings and critically reflect on the overall process and outcomes. The assessment addresses the principles and foundations of data science, statistical methods, data preparation, visualisation, predictive modelling, decision making and the critical evaluation of data science techniques and tools. Students begin by exploring the selected dataset to understand its structure, characteristics and limitations. Although the supplied datasets have already been cleaned, students may undertake additional data preparation or transformation where necessary. Any preprocessing decisions must be justified in relation to the requirements of the selected analytical methods. Feature selection should also be considered as part of preparing the data for model development. The assessment requires students to identify suitable forms of analysis for the selected scenario and justify their choice of methods. At least two different techniques must be used to develop models with predictive capacity for the response variable in the chosen dataset. The models must be trained and tested consistently, using the same training and test datasets so that their performance can be compared fairly. Where appropriate, students should also provide insight into feature importance and explain the contribution of relevant variables to predictive performance. Model performance must be evaluated using suitable metrics, followed by a clear description of the findings and recommendations appropriate for the intended audience. The report should document the complete analytical workflow, including data exploration, preprocessing, feature selection, model development, testing and evaluation. Students are expected to explain and justify the decisions made throughout the process rather than simply presenting code or model results. The assessment also requires students to demonstrate practical proficiency in data science tools and techniques. The brief expects the use of R for completing the assignment and requires evidence of important elements of the code, although the complete code does not need to be submitted. Data visualisation must be used to support the written discussion and communicate relevant findings effectively. The assessment is evaluated across theoretical knowledge and method selection, data exploration and processing, technical application and model evaluation, communication of findings, and overall presentation and referencing. The assessment therefore combines technical implementation with critical analysis, requiring students to explain why particular methods were selected, evaluate their effectiveness and consider the limitations and implications of the resulting findings. A separate second assessment component accompanies the written report. This component requires a presentation of the key findings from the written work using a maximum of five slides and a presentation duration of no more than seven minutes. It should summarise the dataset, methods, key findings and project outcomes while providing critical reflective commentary on lessons learned, factors affecting success and potential real-world applications.

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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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Cryptography 2,500 words

Cryptography – Secure Land Transaction Contract Exchange Protocol

This 2,500-word Cryptography coursework for Coventry University examines the design of a secure communication protocol for the remote exchange and signing of legal property transaction contracts. The assignment is based on a scenario involving Hackit & Run LLP (H&R), a firm of solicitors specialising in property transactions in the UK and overseas. Because property transactions are increasingly conducted through remote communications, H&R intends to establish a comprehensive system for secure document handling, exchange and digital signing that complies with legal requirements and remains enforceable under UK law. The scenario concerns a land transaction between Mrs. Harvey, the buyer, and Mr L.M. Facey, the seller. Students must devise a communication protocol involving three parties: H&R, the seller’s solicitor and Mrs. Harvey. H&R communicates with the seller through the seller’s solicitor rather than directly with the seller. The seller’s solicitor sends the contract to H&R, H&R forwards it to Mrs. Harvey, Mrs. Harvey digitally signs the contract and returns it to H&R, and H&R then sends the signed contract to the seller’s solicitor. The assignment requires students to consider two communication scenarios between H&R and the seller’s solicitor: a situation where the two parties have previously communicated securely and a situation where they are communicating securely for the first time. Students must identify suitable encryption algorithms for the different stages of the contract exchange protocol and justify their algorithm choices. The work should demonstrate an understanding of appropriate cryptographic approaches for maintaining confidentiality, integrity and availability during secure communication. Students must clearly illustrate their proposed protocol using suitable graphics and pseudocode. A full functioning implementation using a programming language may be provided as a higher-level approach. The report must identify the strengths and limitations of the proposed protocol and discuss the findings. This requires students to connect cryptographic theory with a practical security protocol designed for a real-world legal transaction. The coursework assesses knowledge of modern cryptography, including symmetric-key cryptography, key exchange, asymmetric cryptography, digital signatures, digital certificates and authentication. Students are also expected to model, test and assess the suitability of cryptographic protocols and algorithms for different practical requirements and critically evaluate current research and technological developments in cryptography and its applications. The final submission is a written report of 2,500 words, excluding appendices and tables, with properly formatted references. The assignment is categorised as a report and is a normal coursework attempt. The brief does not specify a particular referencing style or academic level, so these fields should not be guessed when entering the assignment into the Reference Library.

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Cryptography 2,500 words

Cryptography – Secure Contract Exchange Protocol

This 2,500-word Cryptography assignment for Coventry University examines the design of a secure communication protocol for the digital exchange and signing of property contracts. The scenario is based on Lauren Order & Cashgrab LLP (LO&C), a UK and overseas property law firm seeking to establish a comprehensive document handling, exchange and signing system that supports remote property transactions while remaining consistent with legal requirements and enforceable under UK law. The assignment requires students to consider the exchange of contracts using the extended CIA model and to devise a secure communication protocol involving three parties: LO&C, the buyer's solicitor Hackit & Run (H&R), and the seller. The scenario specifies that LO&C communicates with the buyer through H&R, that LO&C and the seller collaborate on initial contract drafts, and that LO&C prepares and sends the final contract to the seller for approval and digital signing before forwarding the signed contract to H&R for the buyer's signature. LO&C and H&R have an existing secure communication relationship. A central requirement is the identification and justification of suitable encryption algorithms for the different stages of the contract exchange protocol. Students may select algorithms covered in lectures or undertake additional research to identify alternative algorithms. The report must explain why particular algorithms are appropriate at different stages of the protocol and demonstrate how the selected cryptographic techniques address the practical security requirements of the scenario. The protocol must be clearly illustrated using suitable graphics and pseudocode, with functioning code being an optional higher-level approach. Students are required to identify the strengths and limitations of their proposed protocol and discuss their findings. The assignment therefore combines theoretical knowledge of modern cryptography with practical protocol design and evaluation. Generative AI may be used to create suitable code where permitted, but students must demonstrate their understanding of the code. The assessed learning outcomes cover modern cryptographic concepts and techniques, including symmetric-key cryptography, key exchange, asymmetric cryptography, digital signatures, digital certificates and authentication. Students are also expected to model, test and assess the suitability of cryptographic protocols and algorithms for practical requirements and critically evaluate current research and technological developments in cryptography and its applications.

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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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Entrepreneurship / Business Management / Enterprise 5,000 words

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

This Enterprise Business Start-up assessment requires students to generate an innovative and sustainable business idea and develop it into a comprehensive start-up plan capable of guiding venture creation, attracting customers and supporting external fundraising. The module is assessed through two connected components: a 10-minute business pitch presented to an audience representing angel investors and venture capitalists, followed by a detailed individual business-plan portfolio. Assessment Brief Feb-May 2026 L… The principal written component is a 4,000-word detailed business plan. It begins with an executive summary before examining the proposed business idea, identified market gap, market research and competitor landscape. Students must then define appropriate customer profiles and segmentation, explain the development of the proposed product or service, and construct suitable marketing and communications strategies for reaching the intended market. Assessment Brief Feb-May 2026 L… A substantial part of the business plan focuses on the venture's financial and commercial viability. Students are expected to develop costing, pricing, sales and revenue projections alongside an appropriate business model. They must also identify the founding team, explain relevant roles and demonstrate the core competencies required to launch and develop the business successfully. Financials and business models receive particularly strong emphasis within the marking criteria. Assessment Brief Feb-May 2026 L… The written portfolio also includes a 1,000-word reflective component. Half of this section focuses on the student's fundraising strategy, including suitable funding sources and how potential investors or funders would be targeted, approached and secured. The other half critically reflects on the student's entrepreneurial tendency, personal experience and future skills development. Students are specifically required to complete the General Measure of Enterprising Tendency (GET) self-assessment and incorporate the results into their reflection. Assessment Brief Feb-May 2026 L… Assessment Brief Feb-May 2026 L… Overall, the assessment integrates entrepreneurial opportunity recognition, market analysis, customer segmentation, product development, marketing, start-up finance, business modelling, team capability, fundraising and reflective entrepreneurial development. The accompanying pitch additionally assesses visual quality, creativity, clarity of message, presentation skills, preparedness and professionalism. Assessment Brief Feb-May 2026 L… Assessment Brief Feb-May 2026 L… Important: the document does not explicitly specify a referencing style or academic level, so I would keep those fields as Not specified rather than assume Harvard or Masters.

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Data Visualisation / Business Intelligence 2,500 words

Data Visualisation (BS666) — Business Analyst Client Report: Dashboard Development, Tool Evaluation and Accessibility in Power BI and Tableau

This Level 7 resit assessment takes the form of a single client-facing report written from the position of a qualified business analyst. Rather than assembling semester activities, it asks for one sustained piece of analytical writing that carries a business case from raw open data through to a defended set of visualisations and the decisions they support. The report opens by identifying a data source drawn from an approved open repository and setting out the business problem the client faces. Provenance, structure, granularity and known limitations of the dataset are examined honestly at this stage, since every downstream claim rests on them, and all data is referenced in full — including data appearing inside charts, as the brief specifically requires. The main body works through three connected strands of critical evaluation. The first traces the development sequence of the visualisations themselves: how the data was prepared and cleaned, why particular chart types were selected over the alternatives available, how layout and interactivity were arranged for the intended audience, and how the design changed across iterations once weaknesses became visible. At least three completed visualisations are then evaluated individually and critically — what each one reveals, where each falls short, and what a reader could reasonably conclude from it. The second strand compares Power BI and Tableau as working environments for this specific dataset rather than in the abstract. Data connectivity, transformation and calculation capability, visual flexibility, publishing and sharing, licensing and governance are all weighed against what the client actually needs, with the practical friction encountered during the build reported rather than smoothed over. The third strand addresses accessibility and cognitive processing. It examines how each platform handles colour contrast and colour-vision deficiency, text alternatives, keyboard navigation and screen reader support, and then moves into the perceptual side — pre-attentive attributes, data-ink economy, chart junk, working memory limits and how visual encoding choices either reduce or inflate the effort a reader must spend to extract meaning. The argument connects this directly to decision quality in organisations with diverse analytical literacy. Findings are reported at length and translated into concrete business implications, with a conclusion that states what the client should do and on what evidence. The submission follows the prescribed structure throughout: title page, executive summary, contents, introduction, business problem, main evaluative section, findings, conclusion, Harvard reference list and appendices, presented as a single file for Turnitin.

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Data Mining / Data Science

Customer Service Escalation Risk Analytics Using Data Mining and Machine Learning

This advanced Data Mining assessment applies the Knowledge Discovery in Databases (KDD) process to a real-world customer-service analytics scenario. Acting as a Data Scientist, students analyse a historical Customer Service Escalation Risk dataset to help an organisation reduce serious and legal customer escalations by identifying early signs of dissatisfaction, service bottlenecks and operational risk. The findings are intended to support business decisions relating to staffing, employee training, customer-journey improvement and escalation prevention. The dataset contains information covering customer demographics, account characteristics, communication channels, issue categories, operational measures such as wait times, transfers and SLA breaches, behavioural indicators including sentiment and response delays, and commercial variables such as monthly fees and contract value. The target variable contains four escalation outcomes: No escalation, Minor escalation, Serious escalation and Legal escalation. The first stage requires data exploration, visualisation and summary, including examination of variable distributions, dataset structure, descriptive characteristics and potential data-quality issues. Students then perform appropriate data cleaning, transformation, feature engineering and preprocessing. Particular attention must be given to variables that could introduce prediction leakage because of their meaning, timing or reliability. The supervised-learning component requires development and tuning of predictive models using suitable techniques such as k-nearest neighbours, Decision Trees, Support Vector Machines, ensembles or neural networks. Models must be evaluated using appropriate multiclass metrics and compared systematically, with interpretation of influential features and model behaviour. The assessment also requires unsupervised learning. After removing the escalation target, students apply and compare clustering approaches such as K-Means and hierarchical clustering. Appropriate preprocessing, encoding, normalisation or dimensionality reduction may be used, with visualisations such as PCA, t-SNE or scatterplots used to explore cluster structure and its relationship with escalation behaviour. Overall, the project assesses the student's ability to independently design a coherent KDD workflow, justify analytical decisions, compare alternative modelling approaches and communicate actionable findings to both technical and executive audiences. Overview word count: approximately 350 words. AI-use note: the brief permits AI tools only to assist with small, specific code snippets. Any AI-generated code must be clearly acknowledged and cited, while the submitted coding, analysis, interpretation and decision-making must remain the student's own work.

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Digital Forensics / Cybersecurity 2,000 words

AI-Augmented Digital Forensics Workflow Audit: Feasibility and Risk Assessment of ForensiScan AI

This digital forensics assessment examines the feasibility, reliability and legal risks associated with introducing AI-assisted analysis into a conventional forensic investigation workflow. Students act as a Lead Forensic Consultant assessing a proposed black-box system called ForensiScan AI, which claims to automatically classify illicit images and identify suspicious intent within encrypted messaging applications using Large Language Models. The central objective is to determine whether the efficiency benefits of AI can be achieved without compromising evidential integrity, transparency or legal defensibility. The report maps the proposed AI system across the four stages of the NIST forensic process: Collection, Examination, Analysis and Reporting. For each phase, students identify the data entering and leaving the AI system and determine whether the technology should be used for preliminary triage or as part of final forensic analysis. A major component concerns verification and validation. Because AI systems may hallucinate or misclassify evidence, students must design a ground-truth protocol involving human verification, statistical sampling and known datasets. The assessment also investigates whether AI-generated results can be reproduced reliably when identical evidence is processed again. The report further addresses chain of custody and data integrity, particularly whether AI processing could alter timestamps, metadata or other forensic artefacts. Ethical and legal analysis covers potential model bias, language and contextual limitations, and whether AI-generated outputs could satisfy the requirements of the Daubert Test for expert evidence. Overall, the assessment combines digital-forensic architecture, AI governance, evidential integrity, model validation, legal admissibility and professional accountability. The grading criteria place particular emphasis on forensic soundness, protection against evidence alteration, critical analysis of AI limitations such as hallucination and non-determinism, and professional technical communication. Overview word count: approximately 340 words. AI-use note: the brief permits AI only for limited assistance such as brainstorming risks, structural feedback and grammar refinement. It explicitly prohibits full report generation, unverified forensic claims and using AI to substitute for the student's own final recommendation or verification protocol. Any AI use requires an appendix containing the tool, exact prompts and a human verification log.

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Operations and Supply Chain Management 1,987 words

Supply Chain Analytics and Quantitative Data Analysis for Organisational Decision-Making

This postgraduate individual report focuses on the application of quantitative data analysis to Operations, Logistics and Supply Chain Management decision-making. Students are required to select an organisation from the private, public or third sector and investigate a relevant operational or supply-chain issue using quantitative data. The purpose is to demonstrate how data can be collected, prepared, analysed and interpreted to generate evidence-based insights that may support managerial decision-making. The selected dataset must relate to the organisation's operations or supply chain and may include variables such as revenues, product orders, sales, transportation costs, procurement expenditure, inventory levels or other appropriate quantitative measures. The dataset must contain at least 60 observations, and the analysis must involve at least two variables. Data may be obtained directly from organisations or from recognised secondary-data platforms and databases. The assessment consists of two equally weighted components. Part A – Motivation and Justification for the Analysis requires students to formulate relevant analytical questions and explain their practical importance by linking them to Operations and Supply Chain Management theory and business practice. Appropriate academic, industry and practitioner evidence should be used to justify the selected issue. Research questions may also be translated into testable hypotheses where appropriate. Part B – Execution of the Analysis requires students to answer the identified questions through appropriate statistical techniques. Potential methods include tables, charts, summary statistics, t-tests and regression analysis. Data may first need to be cleaned, transformed and structured before analysis. The results must then be interpreted clearly for a managerial audience such as the organisation's board, owner or CEO. The statistical analysis is expected to be conducted using Stata, with all data-cleaning, manipulation and analytical commands recorded in a reproducible do-file. The report must also demonstrate explicit links between theory and practice and contain a suitable mixture of academic and professional evidence, including at least five academic journal articles. Harvard referencing is required throughout. The resulting work demonstrates practical competence in business analytics, statistical interpretation, supply-chain decision support, reproducible analysis and evidence-based managerial communication. Overview word count: approximately 370 words.

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International Human Resource Management / International Business 801 words

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

This International Human Resource Management assessment examines how cultural, institutional and employment-related factors influence recruitment and international staffing decisions when an organisation expands into a new national market. Students take the role of an HR representative for VetDopomoga, a Ukraine-based international veterinary clinic chain considering expansion into either the United Kingdom or India. The task requires a comparative analysis of Ukraine and the selected host country, followed by evidence-based recommendations for adapting the organisation's recruitment strategy. The first element of the assessment evaluates the cultural and institutional environment of the selected country. Students consider factors such as communication style, hierarchy and power distance, individualism versus collectivism, time orientation, labour-market conditions, professional expectations and the regulatory or employment environment. These factors must be compared with the corresponding context in Ukraine to identify implications for international HR practice. Students must then apply an appropriate international staffing strategy, selecting from ethnocentric, polycentric, regiocentric or geocentric approaches. The selected strategy should be justified in relation to VetDopomoga's proposed international expansion and recruitment requirements. The poster must also apply one cultural framework. Students may use either the Cultural Intelligence Framework developed by Earley and Ang or Erin Meyer's Culture Map. Two relevant dimensions from the selected framework should be analysed to explain potential benefits and challenges for recruitment across Ukraine and the selected host country. Practical application is an important component of the assessment. Students research recruitment best practices used by international veterinary organisations operating in the UK or India and assess which practices VetDopomoga could adopt, modify or avoid. The poster concludes with three evidence-based reasons supporting expansion into the selected country. The final poster should be concise, visually structured and supported by diagrams, charts, icons or other relevant visuals. At least seven academic or professional sources are required, including the core International Human Resource Management textbook, with Harvard-style in-text citations and a full reference list. One important guideline: the assessment brief indicates Category 2 AI use — proofreading only, meaning AI-generated assessment content is not permitted under that category.

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Computer Networks and Network Engineering 3,500 words

Wireless, Cloud and Software Defined Networking: Network Modelling, Emulation and Evaluation

This technical networking assignment focuses on the design, implementation, emulation and evaluation of wireless, cloud and Software Defined Networking environments. It combines practical network modelling with analytical discussion and requires students to demonstrate their understanding of modern networking architectures through Mininet-WiFi, Mininet, cloud deployment technologies and an ONOS Software Defined Networking controller. The first task involves creating an ad-hoc wireless network for an emergency-response scenario. A minimum of three wireless stations must be configured using specified parameters such as transmission range, antenna height, antenna gain, SSID and wireless capabilities. Students are required to explain the network design and implementation, provide the Python configuration script used with Mininet-WiFi, and demonstrate connectivity using ICMP communication between appropriate stations. The second task examines cloud-service emulation. Students must construct a Mininet topology containing a switch and two hosts and deploy a simple static website using Render.com. The task requires evidence of cloud configuration, GitHub repository integration, commands used to provide internet access to the emulated host, webpage access through Xterm, screenshots of the resulting webpage and the associated HTML code. The third task addresses Software Defined Networking (SDN). Students create an emulated environment involving three hosts and three servers, implement the required network topology and use the ONOS controller to provide control-plane programmability. Evidence must include the Python emulation script, ONOS GUI output, host-to-server connectivity testing and TCP transmission testing. The final analytical component requires students to critically evaluate the relationship between Software Defined Networking and Network Functions Virtualisation (NFV) and assess security algorithms used in cloud computing, including a comparison of the advantages and disadvantages of two selected algorithms. The coursework therefore integrates practical network configuration, connectivity testing, cloud deployment, programmable networking and academically referenced technical evaluation. Overview word count: approximately 335 words. Important: the brief explicitly states that AI-generated report or code content is prohibited, so this Reference Library description should be treated only as catalogue/metadata content, not as coursework material for submission.

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Business and Management 34,000 words

Examining the Role of Cross-Cultural Communication in Enhancing Team Efficiency: Evidence from McDonald’s Multicultural Workforce in London

This dissertation examines the role of cross-cultural communication in enhancing team efficiency within McDonald’s multicultural workforce, with the study framed around the challenges and opportunities created by culturally diverse working environments. The research considers how differences in language, communication styles, cultural expectations and workplace behaviour can influence employee collaboration, productivity and organisational effectiveness. The study aims to assess cross-cultural communication within multicultural teams, analyse its relationship with team success, and identify cultural factors that can support stronger workplace collaboration. The research adopts a qualitative secondary-research methodology under an interpretivist and inductive approach. Evidence is drawn from peer-reviewed academic literature, McDonald’s annual and diversity reports, and relevant hospitality-sector studies. The collected evidence is examined through thematic analysis to identify recurring patterns relating to communication barriers, workforce productivity, multicultural collaboration and inclusive leadership. The analysis is organised around four principal themes: cross-cultural diversity and workforce productivity; communication barriers and cultural challenges; diversity management and inclusive leadership; and HR practices, employee motivation and organisational performance. The discussion considers issues such as language barriers, cultural adjustment, misunderstandings, workplace conflict, leadership representation, employee inclusion, recruitment, training, digital HR systems and the use of AI-enabled workforce technologies. The study finds that workforce diversity alone does not automatically generate higher productivity. Instead, the effectiveness of multicultural teams depends substantially on the communication structures, inclusive leadership practices and HR support systems used by the organisation. Effective cross-cultural communication can strengthen coordination, customer responsiveness, employee engagement and operational efficiency, while poorly managed communication differences can contribute to delays, misunderstanding, stress and conflict. The report concludes with recommendations for continued cross-cultural communication training, inclusive leadership development, conflict-resolution initiatives and multilingual communication support. It also recognises the limitation of relying on secondary evidence and identifies primary research with employees and managers as a potential direction for future research. Overview word count: approximately 350 words.

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Business Management / Business Consultancy / Supply Chain Management 5,000 words

Digital Transformation for Sustainable Supply Chain Transparency at Unilever: Blockchain, IoT and AI

This MSc Business Consultancy Project requires students to undertake an evidence-based consultancy investigation addressing a strategically significant business problem within a selected organisation. The assessment is designed to replicate professional consultancy practice by requiring students to define a focused organisational challenge, critically analyse secondary evidence, apply relevant management frameworks, evaluate stakeholder implications and develop practical recommendations that create value for the client organisation. The final submission is a 5,000-word consultancy report, including a 500-word employability reflection. The reference project examines Unilever Plc and focuses on the challenge of improving transparency and traceability across its complex global supply chain. Particular attention is given to the potential application of Blockchain, Internet of Things (IoT) and Artificial Intelligence (AI) to support real-time traceability, predictive analytics, ethical sourcing, operational efficiency and sustainability performance. The project considers how digital transformation could support Unilever's sustainability objectives while responding to growing regulatory, environmental and stakeholder pressures. The consultancy report requires a structured analysis consisting of an executive summary, introduction, company/client overview, clearly defined business problem and consultancy focus, and detailed stakeholder analysis. Students then undertake an extensive data analysis and framework application section using two or three relevant theoretical models alongside credible secondary evidence, industry reports, company data, tables, charts or Excel outputs. Findings should be interpreted critically and linked back to appropriate strategic or management frameworks while incorporating ethical and sustainability considerations. The project concludes with three prioritised, actionable and evidence-based recommendations, including consideration of implementation risks, barriers and anticipated benefits. Students must also critically reflect on the employability skills developed through the consultancy project, including research, analysis, problem-solving, project management, communication, professional behaviour, ethical awareness and future career development. All academic and professional evidence must be cited using the Harvard Referencing System, with emphasis on credible and current sources.

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Computing / Artificial Intelligence / Digital Transformation / Management Consultancy 7,000 words

AI Readiness and Programme Adoption Strategy for the NewFutures: AI Programme at Northumbria University London

This postgraduate consultancy project focuses on developing an AI readiness, skills-development and programme-adoption strategy for students and recent alumni at Northumbria University London. The project supports the university’s participation in NewFutures: AI, a funded AI skills and career-readiness programme offering a four-week online course covering responsible AI foundations and specialist pathways in Marketing and Communications, Finance and Accounting, Business Operations and Logistics, Administration, and ICT and Technical Support. The central consultancy challenge is to understand the AI literacy, confidence, readiness and training needs of Northumbria University London students and alumni and translate that evidence into a practical implementation and outreach strategy. The client aims to reach approximately 12,000 students and recent alumni and support a target of 6,000 LMS registrations during the 2026–2027 programme period. The project requires primary and secondary research into AI readiness, demand for different AI-skilling pathways and barriers to participation such as awareness, time, perceived value and accessibility. The consultancy team is also expected to benchmark comparable initiatives and use research evidence to develop recommendations appropriate to different academic disciplines and student and alumni groups. The implementation component focuses on designing an evidence-based outreach and adoption campaign, including appropriate communication channels, messaging, timing, incentives, faculty engagement and stakeholder participation. Recommended channels may include email campaigns, newsletters, social media, student services, events, learning platforms and alumni communications. The project also requires an implementation timeline and indicative budget for the 2026–2027 programme period. The wider assessment develops professional consultancy capability through business and requirements analysis, research methodology, ethical research practice, practical implementation, testing and strategic recommendations. The project charter additionally establishes milestones for research design, data collection, analysis, report development, review and presentation, together with defined responsibilities for project management, data analysis, AI expertise and stakeholder communication. The individual component complements the consultancy work through critical reflection on personal contribution, skills development, decision-making, problem-solving, communication, collaboration, technical capability, innovation and continuous professional development.

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Artificial Intelligence 2,000 words

End-to-End Applied AI Development — Comparative Machine Learning and Neural Network Modelling on a Public Dataset

This assessment runs a complete applied AI development cycle end to end: problem definition, dataset selection, preprocessing, model building, optimisation, evaluation and critical reflection. Students identify a real-world problem themselves, formulate a research question from it, and source a suitable dataset from a recognised public repository such as UCI, Kaggle, Data.gov or OpenML. Dataset choice carries more weight than students expect. It must be genuinely suitable for supervised learning, complex enough to make preprocessing and feature engineering meaningful, and — critically — structured so that a traditional machine learning approach and a deep learning approach can be sensibly compared on it. A dataset too small or too clean makes the neural network component pointless; one too large or too noisy makes the whole pipeline unfinishable within the page limit. The source must be referenced and the choice explicitly justified against the research problem. The modelling requirement is fixed: at least two supervised machine learning models, plus one artificial neural network built in a mainstream deep learning framework, all trained and tested. The comparison between them is the analytical core of the work. Reporting that the neural network scored higher is not an answer; explaining why, in terms of the data's structure and each model's inductive assumptions, is. Marks are distributed across problem framing, the traditional models, the deep learning model, evaluation and critical analysis including responsible AI considerations, and academic communication. That responsible AI component is easy to overlook and is not decorative — it asks what the model's limitations mean for anyone who might rely on it. Presentation requirements are specific. The report is page-limited rather than purely word-limited, and every plot must be described in the text while also being legible enough to communicate on its own — a common failure is dense default library output pasted in without axis labels or scale. The implementation is documented in a notebook combining markdown and code cells so the development process is visible, not just the final result, and submissions typically include the cleaned dataset alongside the code. The strongest submissions treat the notebook and the report as one argument. Weaker ones produce a working notebook and then write a report that describes it, rather than a report that uses it as evidence. Our support on assessments of this type is guidance-based. Typical areas of help include: advising on whether a candidate dataset can actually support the required model comparison, explaining how to justify preprocessing decisions, clarifying which evaluation metrics suit which problem type and why accuracy alone is often misleading, showing how to structure a critical limitations and responsible AI discussion, checking Harvard referencing, and reviewing a student's own draft against the published marking criteria.

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Entrepreneurship and Business Start-up 5,000 words

Enterprise Start-up Portfolio — Business Plan, Fundraising Strategy and Entrepreneurial Self-Assessment

An enterprise start-up portfolio assessment asks students to originate a business idea and build the full supporting case for it, then present that case both in writing and as a recorded investor pitch. It is a pass/fail module structure in which every component must be passed individually — a strong business plan cannot compensate for a weak pitch, or vice versa. The written portfolio divides into two unequal halves. The larger part is the business plan itself, built to a fixed section structure with prescribed word allocations: an executive summary; the business idea set against an identified market gap, with market research and competitor analysis; customer profiles and segmentation; product development; marketing and communications; financials and business models covering costing, pricing, sales and revenue; and the founding team with its core competencies. The word allocations are not decorative — financials carry the single largest weighting in both the word budget and the marking rubric, which tells students where analytical depth is expected and where concision is. The smaller part is reflective. It covers the fundraising strategy — which funding sources are realistic for this venture, and how each would be targeted, approached and secured — and the student's own entrepreneurial tendency, informed by a standardised self-assessment instrument taken online. The rubric here rewards critical self-reflection over description: reporting a test result scores poorly; interpreting what the result means for how this founder should build a team and where they need support scores well. The pitch component is assessed on visual and audio quality, content and message, comprehension, delivery, and evident preparation. Technical execution carries real marks, which students routinely underestimate. Two things separate strong submissions. The first is internal consistency: the revenue model must follow from the pricing, the pricing from the customer segment, the segment from the identified gap. Plans that read as seven separate essays under seven headings lose marks even when each section is individually competent. The second is specificity in the financials — costing assumptions stated and justified, rather than round numbers presented without derivation. Note that assessments of this type commonly require the student to retain all drafts and earlier versions of their work, and to sign a detailed declaration itemising exactly how any AI tools were used. Our support on assessments of this type is guidance-based. Typical areas of help include: explaining what a market gap argument needs to be credible, showing how competitor analysis should be structured rather than listed, clarifying how costing and pricing assumptions should be built and presented, reviewing whether a fundraising strategy matches the venture's actual stage, explaining how reflective writing is assessed at postgraduate level, and checking a completed draft against the published rubric.

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Enterprise Start-up Portfolio — Business Plan, Fundraising Strategy and Entrepreneurial Self-Assessment