Data Science & Analytics MSc

You will study 180 or 185 credits in total during your Data Science and Analytics MSc. A standard module is typically worth 15 credits and the research project is worth 60 credits. These are the modules studied in 2018. If you are starting in September 2019, these will give you a flavour of the modules you are likely to study. All Modules are subject to change.


Compulsory modules

Dissertation in Data Science and Analytics - 60 credits

This module will prepare students for data science project assignment and dissertation writing. This module brings together all the skills and knowledge that the students have gained in the MSc Data Science and Analytics taught programme.

Learning Skills through Case Studies - 15 credits

This module will develop skills which will be useful preparation for the dissertation, potential further research, and in employment. This will include presentation skills and teamwork, some of which will be developed through real-life case studies.

Data Science - 15 credits

The aim of the module is for students to understand methods of analysis that allow people to gain insights from complex data. The module covers the theoretical basis of a variety of approaches, placed into a practical context using different application domains.


Optional modules include 

Data Management - 15 credits

This module covers the principles of the design and implementation of database management systems, including the theory of relational databases and E-R modeling; and the use of SQL to create and manipulate data in a database.

Statistical Theory and Methods - 15 credits

This module gives an introduction to the basics of statistics, aimed at students who did not take any statistics modules during their undergraduate degree.  This module is to give a general unified theory and method of estimation and hypotheses testing, and to introduce Bayesian inference and the comparison with classical inference.

Statistical Learning - 15 credits

Statistical learning is a way to rigorously identify patterns in data and to make quantitative predictions. It is how we translate data into knowledge. In this module the fundamental concepts of statistical learning are introduced and the student will learn to use several key statistical models widely employed in science and industry.

Business Analytics and Decision Science - 15 credits

This module aims to introduce students to key concepts in business analytics, with a special emphasis on common areas of application. It also explores the links between the behavioural (decision science) perspective on decision support and the management science/business analytics perspective. Students will explore and comment on the emerging role of ‘big data’ and learn to display familiarity with major areas of application of business analytics.

The full list of optional modules can be read in the course catalogue.