MATH5872M Dissertation in Data Science and Analytics
60 Credits Class Size: 150
Module manager: Luisa Cutillo
Email: mscstats_dsa@leeds.ac.uk
Taught: 1 Jun to 30 Sep, 1 Jun to 30 Sep View Timetable
Year running
2025/26
This module is not approved as an Elective
Module summary
This module will prepare students for project work in data science. This module brings together all the skills and knowledge that the students have gained in the MSc Data Science and Analytics taught programme. Students will develop independent working skills and communication skills through working on a project and presenting the results.
Objectives
On completion of this module, students should be able to:
a) complete with guidance the planning, execution and maintenance of a data science project;
b) effectively present the outputs of their project in the appropriate context.
Learning outcomes
Transferable Skills:
- Investigate and understand a data science problem;
- Mathematical type-setting;
- Presentation and communication;
- Programming.
Syllabus
Each student will be supported through a suitable project in data science. The title and objectives of the project will be approved by the Module Leader. As far as possible, the projects will reflect the particular interests of individual students. Projects in different topics as well as different styles will be available to meet students’ interests.
Teaching Methods
| Delivery type |
Number |
Length hours |
Student hours |
| Meetings |
6 |
1 |
6 |
| Private study hours |
594 |
| Total Contact hours |
6 |
| Total hours (100hr per 10 credits) |
600 |
Private study
Reading relevant background material, writing outputs that effectively demonstrate understanding of the project elements, and performing computations and analyses as required with support.
Opportunities for Formative Feedback
Monitoring by regular project meetings.
Methods of Assessment
Coursework
| Assessment type |
Notes |
% of formal assessment |
| Project |
Students will conduct an independent project where their findings are assessed via a selection of outputs which may include written reports, presentations, interviews, posters, reflective logs, notes of supervision meetings or other outputs relevant to the project. The detail of outputs required and their contribution to the overall module assessment will be detailed in the module handbook. |
100 |
| Total percentage (Assessment Coursework) |
100 |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading List
Check the module area in Minerva for your reading list
Last updated: 12/05/2026
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