Data-Intensive Analysis (Taught)

The MSc in Data-Intensive Analysis is an interdisciplinary course providing students with an understanding of how data is used to gain useful insights in all areas of scientific endeavour. The programme has a substantive statistical component – both theory and practice – allied to computational data science and visualisation.

Compulsory modules:

1. Introductory Data Analysis
2. Advanced Data Analysis
3. Knowledge Discovery and Datamining
4. Applied Statistical Modelling using GLMs

Optional modules. Students choose four of the following optional modules.

1. Computing in Statistics
2. Data-Intensive Systems
3. Information Visualisation
4. Masters Programming Projects
5. Object-Orientated Modelling, Design and Programming
6. Programming Principles and Practice
7. Software for Data Analysis

Project:
During the second semester, students work with staff to define and agree upon a topic for the extended project, which they will work on during the final three months of the course, and which culminates in a 15,000-word dissertation. Dissertation projects may be group-based or completed individually (students are assessed individually in either case).

The dissertation typically comprises:

• a review of related work
• the extension of existing or the development of new ideas
• software implementation and testing
• analysis and evaluation.

Students are required to give a presentation of their work in addition to the written dissertation.

Each project is supervised by one or two members of staff, typically through regular meetings and reviews of software and dissertation drafts. Supervisors and topics may be from either of the schools of Computer Science or Mathematics and Statistics and many are in collaboration with companies or other external bodies.

If students choose not to complete the dissertation requirement for the MSc, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Diploma instead, finishing the course at the end of the second semester of study.

Most modules are assessed through practical coursework exercises and examinations.