LDSCI7237 Artificial Intelligence Dissertation Project Course Descriptor

Course Summary

This course provides students with the opportunity to complete an MSc dissertation project addressing a substantial, real-world problem. The project can cover a wide spectrum of topics taught in the programme: from ethical and philosophical issues surrounding AI and data science, to applied machine learning, to developing a software artefact (e.g., a software library). All projects, however, must have an element of data, AI, software, and a “human face”, building upon the variety of material being taught during the programme. There is a particular focus on sustainable development in terms of resource efficiency as well as societal, economic, and environmental impact.

The project may also be interdisciplinary in nature, for example, solving a problem in digital humanities or computational social sciences using data analytics and machine learning. Such interdisciplinary projects get assigned two supervisors: (i) an expert from the humanities discipline who will guide students to solve a non-trivial problem; and (ii) an expert in computer or data science who will guide students to develop a non-trivial solution.

After an initial group seminar with the course leader, students meet with their assigned supervisor(s) to finalise the subject of their project and discuss and refine its requirements. Once the dissertation has been submitted, students defend it in a 30-minute presentation and demonstration.

Course Aims

The aims of the course are:

• Extend students’ ability to devise original solutions for a particular problem of their choice.
• Extend students’ ability to organise and manage a project from start to finish.
• Extend students’ ability to present clearly their ideas, choices and evaluation methodology to their peers.
• Prepare students for a wide range of careers and roles in society.

Learning Outcomes

On successful completion of the course, students will be able to:

Knowledge and Understanding

Subject Specific Skills

Transferable and Professional Skills

Teaching and Learning

Teaching and learning strategies for this course will include: 

• Group seminars
• Independent (though guided) study and research
• Individual supervision, which supports both writing and oral communication skills
• Individual written feedback
• Online discussion forum

Course information and supplementary materials are available on the University’s Virtual Learning Environment (VLE).

Students are required to attend and participate in all the formal and timetabled sessions for this course. Students are also expected to manage their directed learning and independent study in support of the course.

Employability Skills

The individual dissertation project cultivates the following employability skills: 

• Research skills: gather requirements, ideas and material and combine them to propose a novel solution; conduct research and explore relevant existing works; solve problems through logical reasoning and rigorous testing.
• Leadership skills: work independently, creatively and to deadlines; and engage in collaborative and constructive discussions with peers.
• Communication skills: communicate findings in a clear, structured manner both orally, via presentation and demonstration, and in writing, via technical documentation.

Assessment

Formative

Students will be formatively assessed during the course as they produce successive drafts of their dissertation and, if applicable, software artefact(s). These do not count towards the end of year results, but will provide students with developmental feedback, both written and oral. 

Summative

Assessment will be in three forms:

The project’s dissertation, any accompanying artefacts and the presentation will be assessed in accordance with the assessment aims set out in the Programme Specification.

Feedback

Students will receive formal feedback in a variety of ways: written (in comments on draft material, including via email correspondence); oral (within one-to-one supervision tutorials and on an ad hoc basis).

Indicative Reading

Reading is to be decided upon between student and supervisor, depending on the topic of the chosen dissertation project.

Indicative Topics

The topics covered by students will vary across projects, but typically a student will encounter (one or more times) the following topics during the project:

• Problem statement definition
• Independent development of a solution or hypothesis
• Defending proposed solution or hypothesis with supporting evidence
• Writing up
• Submission
• Presentation, or demonstration, or both