Program Overview

MSc Data Science and Machine Learning Project (COMP0158)

Key Information

The MSc Data Science and Machine Learning Project is offered by the Faculty of Engineering Sciences, with the Computer Science department serving as the teaching department. This module has a credit value of 60.

Restrictions

Module delivery for PGT (FHEQ Level 7) is available on MSc Data Science and Machine Learning.

Alternative Credit Options

There are no alternative credit options available for this module.

Description

Aims

The module aims to give students experience of undertaking and completing a large piece of work, applying techniques learned throughout the programme, including the technical skills of analysis, design, and implementation.

Intended Learning Outcomes

On successful completion of the module, a student will be able to:

• Work individually developing a major project.
• Plan and coordinate development activities.
• Make realistic work commitments.
• Present the work done effectively to a deadline.

Indicative Content

There is no set syllabus: students identify their chosen project area and are allocated a Project Supervisor who is a member of academic staff. The supervisor provides support and guidance. The project runs from immediately after the central assessment period (May/June); students are responsible for organising themselves and their work, with advice from their supervisor. Students are expected to meet with their supervisor on a regular basis, as agreed with the supervisor. Some projects are done in conjunction with other departments of the College, others are done in conjunction with external organisations subject to approval by the department. In all cases, at least one supervisor must be from within the department who will provide, as a minimum, project management advice.

Project Report

The main report documents the results of the project. The deadline for submission is normally in early September.

Formatting Details

The dissertation text (defined as everything except title page, table of contents, references, and appendices) should typically be between 30 and 100 pages in 12-point type and 1.5 or double spacing. The total dissertation length (main text together with appendices) should under no circumstances exceed 120 pages. Students should place their code in an online repository and provide access details to it in their dissertation. Writing the dissertation in LaTeX is optional, but strongly recommended.

Requisites

To be eligible to select this module, a student must be registered on a programme and year of study for which it is formally available.

Module Deliveries for 2026/27 Academic Year

Intended Teaching Term

Terms 2 and 3, Postgraduate (FHEQ Level 7).

Teaching and Assessment

Mode of Study

In person.

Methods of Assessment

100% Dissertations, extended projects, and reports.

Mark Scheme

Numeric Marks.

Other Information

Number of Students on Module in Previous Year

Module Leader

Dr Eddie Edwards.