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Time Series Modelling
Time Series Modelling Case Study – Oil Price Forecasting
This individual Time Series Modelling Case Study focuses on analysing and forecasting oil price data using established time-series techniques and an alternative modelling approach. The assessment requires students to work with daily oil price information covering the period from 2024 to 2026 and investigate the underlying patterns, stationarity and forecasting behaviour of the data. The first part of the assignment involves exploratory data analysis and time-series modelling using an ARMA-based approach. Students are required to create appropriate visualisations of the data, perform exploratory analysis and conduct tests for non-stationarity, including relevant stationarity diagnostics such as ADF, ACF and PACF analysis and differencing where required. An ARMA model must then be defined, with suitable model parameters identified using the AIC likelihood approach. The assessment requires the student to examine possible combinations of model parameters, assess model residuals, evaluate model performance using appropriate metrics such as RMSE, and produce forecasts extending 24 months into the future. Confidence intervals must also be included with the forecasts. The second part requires students to investigate an alternative modelling solution for the same oil-price time-series data. Possible approaches discussed in the assignment include models such as LSTM and Prophet. Students are expected to conduct a literature review relating to the selected alternative model, build and apply the model, tune relevant hyperparameters where appropriate, generate 24-month forecasts, create suitable visualisations and calculate appropriate evaluation metrics. The final part of the assessment requires a 6–8 page report describing the modelling process, forecasts, analysis and inferences. The report should explain the reasoning behind the analytical and modelling choices rather than simply presenting numerical results. Students are expected to critically discuss why particular approaches were selected, how the modelling decisions may have influenced the results, how forecasts compare with subsequently collected real data where available, and what improvements could be made in future work. The assessment evaluates both the technical implementation and the quality of the written analysis. The code component assesses completion of the modelling and forecasting tasks, stationarity testing, the alternative solution, code quality and annotation. The report component assesses discussion of the analysis and inferences, comparison of the modelling approaches, clarity of interpretation, report structure, appropriate use of figures and suitable academic references. The submission consists of a report in PDF or Word format, with the code submitted separately or through an appropriate repository.
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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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Research Methods / Project Management / Computer and Information Sciences
3,000 words
Critical Literature Review in Research Methods and Project Management
This Research Methods and Project Management assessment develops students’ ability to search for, evaluate, critically analyse and synthesise academic literature within a computing or information-science research area. Students work within an allocated group to conduct a structured literature search and critically evaluate research papers relevant to an assigned theme, before using the combined group literature corpus to produce an individual literature review. KF7028 - Assessment 1 - Semeste… Each group member must identify and critically analyse a minimum of five academic papers using the supplied Critical Paper Summary template. These individual summaries are then combined into a single group document and shared so that all team members can use the collective body of research. The quality of this component depends on the relevance and academic quality of the selected papers and the depth of critical evaluation rather than simple description. KF7028 - Assessment 1 - Semeste… The main individual component is a 3,000-word critical literature review, worth 60% of the assessment. Students must use the literature identified and summarised through the group activity and critically discuss the research associated with their allocated topic. The review should synthesise the literature into a coherent discussion rather than presenting disconnected paper summaries, demonstrating criticality, clear structure and effective academic writing. KF7028 - Assessment 1 - Semeste… A further 20% is awarded for an individual research and meeting log, maintained through Blackboard. Students are expected to record their research progress, contribution to the group, approach to collaboration and reflections on the literature-review process. Stronger logs demonstrate detailed evidence of active participation, reflective insight and professional collaboration rather than merely listing completed tasks. KF7028 - Assessment 1 - Semeste… KF7028 - Assessment 1 - Semeste… The assessment directly evaluates the ability to apply project-management principles to a computing-related research activity and to search, evaluate and develop a critical literature review. Wider module outcomes also emphasise research techniques, data and information analysis, professional research practice, ethics, risk, legal issues, societal considerations and sustainability. KF7028 - Assessment 1 - Semeste… The marking structure allocates 20% to the combined critical paper analysis, 20% to the research/meeting log and 60% to the individual literature review. Higher-performing work is expected to use high-quality and directly relevant academic sources, demonstrate strong critical analysis, synthesise evidence across the research theme, maintain a professional academic structure and apply accurate Harvard referencing throughout. KF7028 - Assessment 1 - Semeste… KF7028 - Assessment 1 - Semeste… Important for the public Reference Library: the brief states that ChatGPT or other AI tools must not be used to generate text or fill in assessment-template sections. Any AI use that supports the work or thinking must be declared, referenced and accompanied by a prompt log in an appendix. Therefore, this entry should be used only as a high-level public description of the assessment rather than as directly submissible student content. KF7028 - Assessment 1 - Semeste…
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Data Science / Time Series Analysis / Machine Learning
Time Series Modelling Case Study: Oil Price Forecasting with ARMA and Alternative Models
This Time Series Modelling Case Study requires students to analyse real-world oil-price time-series data and develop forecasting models capable of predicting future values. The assessment combines traditional statistical time-series techniques with an alternative forecasting approach, requiring students to demonstrate practical modelling skills, critical research engagement and evidence-based interpretation of forecasting results. The coursework is completed individually and contributes 40% of the assessment. assing,,, (1) The assessment is divided into three main parts. Part 1 focuses on developing an ARMA-based forecasting model using daily oil-price data covering approximately 2024 to 2026. Students begin with exploratory data analysis and initial visualisation before testing whether the time series is stationary. Where necessary, appropriate transformations or differencing must be applied to obtain stationarity. Students then define an ARMA model and identify suitable p, d and q parameters using an AIC-based model-selection procedure across the parameter ranges specified in the brief. assing,,, (1) Model adequacy must be assessed using diagnostic analysis. Students inspect residuals, generate additional ACF plots, examine residual distributions and evaluate prediction performance using appropriate metrics such as RMSE. The selected model is then used to forecast oil prices 24 months into the future, with appropriate confidence intervals added to communicate forecast uncertainty. assing,,, (1) Part 2 requires students to research and implement an alternative forecasting approach. Suggested examples include LSTM and Prophet, although another appropriate model may be proposed. Students conduct a literature review supporting the alternative method, build and where relevant hyperparameter-tune the model, generate another 24-month forecast, visualise predictions and confidence intervals, and calculate suitable evaluation metrics. This component is intended to demonstrate independent research and the ability to propose an alternative solution rather than relying only on the conventional ARMA approach. assing,,, (1) Part 3 consists of a 6–8 page technical report explaining the modelling process, forecasting results and resulting inferences. The report should provide a critical analysis rather than simply reproducing numerical outputs. Students are expected to explain why results occurred, justify modelling choices, evaluate how those choices influenced performance, compare forecasts with subsequently observed real data where possible, and construct a coherent narrative supported by plots, images, summary statistics and academic literature. Future improvements to the modelling approach should also be critically discussed. assing,,, (1) Submission consists of both the report and working code. The code may be submitted directly or through an accessible Colab or GitHub repository and must reproduce all models, figures and numerical results presented in the report. The assessment allocates 60% of the marks to code and 40% to the report. Within the coding component, modelling and forecasting completion accounts for 40 marks and code quality and annotation for 20 marks. The report is assessed on analysis and inference, methodological justification, comparison of the two modelling approaches, presentation quality, figures and use of appropriate references. assing,,, (1) Key technical expectations include appropriate testing for stationarity, use of methods such as ADF, ACF, PACF and differencing, systematic model selection, forecasting, evaluation and clear comparison between the traditional ARMA model and the chosen alternative approach. Higher-quality work is expected to interpret what the forecasts mean, identify potential improvements and demonstrate sound technical communication rather than merely reporting model outputs. assing,,, (1) Important for the public Reference Library: the brief explicitly states that students must not use generative AI to write the report, and the rubric indicates that AI text-generation use may result in zero marks for the whole assignment. Therefore, the public entry should remain a high-level description of the assessment rather than material intended for direct submission. assing,,, (1)
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Computer Science / 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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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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Computer Science
2,800 words
Specialism Research Report
The Specialism Research Report is an individual assessment for the Advanced Research Topics in Computer Science module. The assignment provides students with an opportunity to develop a deeper understanding of a selected computer science research specialism and to investigate an open research question within that area. The available research specialisms are Artificial Intelligence, Networking, Cyber Security, Software Engineering and Data Science. Students are expected to examine the research specialism associated with their degree route and develop their understanding of current research challenges, established techniques and potential future research directions. The report requires students to provide an overview of the research paper presented in the relevant 7COM1084 Research Specialism Lecture. The report must identify and explain the research question addressed by the specialist paper, consider why the research problem is scientifically interesting or relevant to a real-world application, and investigate possible approaches for addressing the question. Students must also identify further research that could build upon the existing work and consider their own personal strengths, interests and experience in relation to the proposed research. The report is structured into five main sections. The first section, Introduction of Research Specialism, provides a general overview of the selected research area and is intended to be accessible to readers with broad computer science knowledge. The second section, Open Research Question, identifies and explains the research problem discussed in the specialist lecture paper and considers its scientific or practical significance. The third section, Existing and Related Work, provides a literature review of research beyond the specialist paper, identifies limitations in existing approaches and discusses related open research problems. The fourth section, Research Approach, examines the methods used in the specialist paper, evaluates their strengths and weaknesses, and proposes an approach for extending the research. The fifth section, Personal Investment, explains the student's interest in the research question and evaluates their personal strengths and experience relevant to conducting the proposed research. Students are expected to use module reading materials and secondary research to support their discussion. The report must use Harvard referencing and include at least 20 references, including the 7COM1084 specialist paper. The references are excluded from the word count. The submission must not exceed 2,800 words, with a permitted range of ±10%. The assessment develops students' ability to understand established research techniques, identify research problems from relevant literature, propose alternative solutions, critically evaluate research literature, develop approaches for future research and communicate research knowledge effectively in a scholarly manner.
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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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Computer Science / Research Methods
500 words
Interim Report: Systematic Literature Review Research Protocol
This postgraduate computer science assignment requires students to prepare an Interim Report establishing the research protocol for a systematic literature review. The assessment focuses on whether the proposed research question is suitable for computer science research, clearly formulated, appropriately motivated by existing literature, and capable of being investigated through a systematic review. The main body of the report must not exceed 500 words, while supporting evidence may be provided separately where appropriate. The report is structured around three main chapters. Chapter 1 introduces the selected research area and summarises the purpose and structure of the report. Chapter 2 provides relevant background and a brief history of the chosen research domain, identifies the problem being addressed, and supports the discussion with at least two relevant academic citations. Chapter 3 presents the formal Literature Review Protocol, including the research question, its context, and the associated PICO elements: Population, Intervention, Comparison and Outcome. Students must also develop and test a Boolean search string using IEEE Xplore and report the number of papers returned by that search. The search strategy is accompanied by explicit inclusion and exclusion criteria governing which studies will be considered for the review. The supplied protocol template requires students to document these elements through two structured tables: one covering the research question and PICO framework, and another recording the search string, paper count, and study-selection criteria. The assessment places significant emphasis on methodological consistency. The research question, PICO elements, search strategy, paper count and inclusion/exclusion criteria must align logically with one another. Students are also assessed on the justification and motivation of the research question, document structure, presentation quality, spelling, grammar and academic referencing. The report must include a title page, table of contents, bibliography and the required research-protocol tables. Harvard referencing is required for both in-text citations and the final reference list. Overall, the assignment develops the foundational skills required for conducting a rigorous systematic literature review, including research-question formulation, structured evidence searching, transparent study-selection procedures, academic justification and professional research reporting.
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Computer Science
1,700 words
Systematic Literature Review — Final Report with Data Extraction and Synthesis
A Research Methods final report at postgraduate computer science level is a systematic literature review written to a defined protocol. Unlike an essay, the method itself is assessed: markers re-run the student's search string and check that the number of papers returned matches what the report claims, so the process must be reproducible rather than merely described. The report is typically built in five chapters. Chapter 1 introduces the research area and states that a literature review is the chosen method. Chapter 2 gives the background, with citations behind every claim or assertion. Chapter 3 sets out the research protocol — the research question decomposed through PICO (population, intervention, comparison, outcome), the search string, and explicit inclusion and exclusion criteria. Chapter 4 presents the results: a data extraction table holding direct quotations and references from each included paper, followed by a data synthesis table that groups those extractions into cross-cutting themes. Chapter 5 concludes by answering the research question from the Chapter 4 evidence alone. Several requirements catch students out. The word limit applies to the main body only — tables, figures, references and appendices sit outside it, which changes how the argument should be distributed. Screenshots and supplementary search strings belong in appendices, not the body. Where an interim report has already been submitted and marked, the final report must visibly incorporate that formative feedback rather than reproduce the earlier chapters unchanged. File naming and file completeness are often mark-bearing in their own right, with missing files scored at zero. Presentation carries weight too: consistent heading and font usage, labelled tables and figures, and error-free spelling and punctuation. The most common conceptual error is treating Chapter 4 as a narrative summary of each paper in turn. A synthesis groups evidence by theme across papers and answers the question; a summary walks through the reading list. A related error is a research question that the background has not motivated — the introduction and background should make the question feel necessary before the protocol formalises it. Our support on assessments of this type is guidance-based. Typical areas of help include: explaining how to decompose a research question using PICO, reviewing whether a search string is syntactically valid and whether inclusion criteria genuinely follow from the question, showing how extraction tables feed into synthesis tables, clarifying Harvard referencing conventions, checking report structure and formatting against the specification, and reviewing a completed draft against the published marking criteria before submission.
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Research Methods (Computer Science / Systematic Literature Review)
500 words
Interim Report – Research Methods (7COM1085)
This assignment is an Interim Report for the Research Methods module (7COM1085). The purpose of the report is to demonstrate that the research team has identified a suitable Computer Science research topic and developed a systematic literature review protocol that can be used for the final dissertation or research project. Students are required to formulate a clear and well-justified research question, define the associated PICO (Population, Intervention, Comparison, Outcome) elements, create an IEEE Xplore Boolean search strategy, and establish appropriate inclusion and exclusion criteria for selecting academic literature. The report must also provide background information on the chosen research area and justify the importance of the research question using relevant scholarly sources. The interim report should follow a structured academic format consisting of an Introduction, Background, Literature Review Protocol, and Bibliography. Students must use Harvard referencing throughout the report and ensure that all citations are properly integrated within the text. The report should demonstrate consistency between the research question, search strategy, and selection criteria while maintaining a professional academic presentation. The main body of the report must not exceed 500 words, although supporting materials such as search results, screenshots, and other evidence may be included in appendices. The assignment is designed to assess students' understanding of research methodologies, systematic literature reviews, critical analysis of academic sources, and their ability to design a rigorous research protocol for a Computer Science investigation.
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