Module manager: Dr Mark Walkley
Email: M.A.Walkley@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2026/27
COMP3931
This module is not approved as a discovery module
This individual project represents the culmination of three years of computer science study and is explicitly centred on artificial intelligence. It provides students with the opportunity to demonstrate advanced mastery of AI concepts, methodologies, and applications. Students undertake a comprehensive exploration of engineering analysis and design within the context of intelligent systems, developing strong competencies in problem formulation, solution design, implementation, and critical evaluation. The module places significant emphasis on the practical application of artificial intelligence theories and techniques to address complex, contemporary, real-world challenges, fostering innovation, creativity, and independent thinking. As an advanced capstone module, students are required to identify and focus on a well-defined artificial intelligence problem, supported by rigorous research and critical analysis. They must apply appropriate AI tools, algorithms, and engineering methodologies to design, develop, and evaluate innovative solutions, demonstrating both technical depth and professional judgement.
This module aims to enable students to consolidate and extend three years of computer science study through the independent design, development, and evaluation of a substantial artificial intelligence–focused project. Students will apply advanced AI theories, tools, and methodologies to a well-defined problem, demonstrating technical competence, critical analysis, and professional-level problem-solving within an applied engineering context.
On successful completion of the module students will be able to:
define and analyse a complex real-world problem to design and implement an artificial intelligence solution applying appropriate engineering design principles and engineering management processes to ensure quality and manage risk. (C1, M1, C2, M2, M3, M3, C5, M5, C6, M6, C9, M9, C14, M14, C15, M15)
identify and discuss legal, ethical, social, professional and sustainability issues relating to the artificial intelligence in the context of the project. (C8, M8)
select and interpret sources of information to solve complex real-world problems. (C4, M4)
apply industrial best-practice, in the development of a solution considering security, sustainability and engineering design lifecycle. (C7, M7, C10, M10, C15, M15)
select and use tools to design, implement, test, analyse and evaluate artificial intelligence project artefacts and identify limitations (C12, M12, C13, M13)
communicate effectively complex topics concerning computer systems to technical and non-technical audiences. (C17, M17)
reflect on their level of mastery of subject knowledge and skills and plan for personal development. (C18, M18)
On successful completion of the module students will be able to:
Formulate and scope a complex artificial intelligence problem, translating real-world requirements into clear technical objectives and success criteria.
Design, implement, and evaluate an AI-based solution using appropriate tools, algorithms, and methodologies, applying systematic testing and performance analysis.
Critically analyse and justify design decisions through the evaluation of alternative approaches, experimental results, and relevant academic literature.
Communicate effectively the project aims, methodology, outcomes, and limitations through a professional technical report and oral or visual presentation, suitable for both academic and non-academic audiences.
Students will conduct an individual project, supervised by an academic member of staff, allowing them to pull together the knowledge and skills gained during their programme of study focusing on the application of knowledge and understanding relating to artificial intelligence.
Projects will require students to undertake practical work resulting in the creation of an artefact and will require all aspects of the implementation lifecycle.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Supervision | 6 | 1 | 6 |
| Lectures | 6 | 1 | 6 |
| Private study hours | 388 | ||
| Total Contact hours | 12 | ||
| Total hours (100hr per 10 credits) | 400 | ||
Students will receive regular supervision where feedback on the progression towards the learning outcomes will be provided.
Students will submit an Outline and Plan in the early stages of their project and receive feedback from an assigned assessor.
Check the module area in Minerva for your reading list
Last updated: 30/04/2026
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