Course Overview

As technology advances, the ability to generate, capture and analyse data from various sources and applications is vital across numerous industries. Our MSc Data Science teaches you how to apply critical mathematical thinking to several data types. You will have skills valuable to financial, social, policy and commercial settings.

The programme will cover data analysis, machine learning, and visualisation, as well as the necessary technical skills to thrive in industry. We will also equip you with the skills needed to stay abreast of data science changes and work in commercially, ethically, and legally appropriate ways.

You will begin by taking modules in programming, data analytics techniques and the fundamentals of mathematics for data science. You further apply these skills in machine learning and data visualisation. You will benefit from emphasising real-world workflows and applying techniques, using case studies, and working with real data sets. You will then have a chance to consolidate and demonstrate the skills you have acquired throughout the year in your final project.

After the programme, you can undertake an industrial placement year, allowing you to gain valuable work experience relevant to your career aspirations. 

We deliver all computing programmes in an active blended learning style, with most lectures replaced by workshops and seminars. Our approach provides a learning environment focused on collaborative working in practical lab spaces, immersed in an environment based on working in the IT industry.

General Eligibility

You should usually hold a second-class honours degree (certain programmes may require a 2:1) from a recognised British or overseas university.

Specific entry requirements

UK degrees: 2:2 STEM, preferably computer science, maths
or statistics.

Part Time Work Details

20 Hours of Work permit weekly for international students.

Language Requirement

• If English is not your first language, an IELTS score of 6.5 (including a minimum of 5.5 in each component) or equivalent is normally required.