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School of Engineering and Informatics (for staff and students)

Dissertation (MRes Advanced AI) (987G5)

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Dissertation (MRes Advanced Artificial Intelligence)

Module 987G5

Module details for 2024/25.

90 credits

FHEQ Level 7 (Masters)

Module Outline

The dissertation project provides the opportunity for an in-depth investigation into a particular problem within the domain of artificial intelligence. Students are supported to creatively tackle a challenge that has a high-level of complexity and should either lead to theoretical contributions to a subfield of AI or employ advanced AI methods to address interdisciplinary or industrial problems. Students will develop their technical skills and knowledge as well as their communication and critical analysis skills. In this research project, students will work in a self-directed manner and manage their own time and exercise initiative and personal responsibility for the project. A primary technical supervisor will be identified to provide advice on the student’s direction and progress.

Module learning outcomes

Demonstrate self-direction in synthesising understanding of knowledge from various sources in order to select appropriate methods and justify design decisions.

Apply the scientific process systematically and rigorously to develop and implement an AI solution to a research problem.

Evaluate and critique the appropriateness and performance of methods for a given application whilst demonstrating an awareness of broader implications of the choice of methods.

Communicate a complex development or research idea in a concise manner, clearly articulating core concepts and supporting results.

Clearly structure the detailed communication of a substantial research project in a manner appropriate for the field of research.

Demonstrate a detailed understanding of the developed solution including any limitations and directions for further research.

TypeTimingWeighting
Dissertation (12000 words)Summer Vacation Week 13 Tue 16:0080.00%
Coursework20.00%
Coursework components. Weighted as shown below.
Oral assessmentVACATION Week 13 (30 minutes)100.00%
Timing

Submission deadlines may vary for different types of assignment/groups of students.

Weighting

Coursework components (if listed) total 100% of the overall coursework weighting value.

TermMethodDurationWeek pattern
Spring SemesterSeminar1 hour10000010000

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Dr Ivor Simpson

Assess convenor
/profiles/504012

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School of Engineering and Informatics (for staff and students)

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