Applied Data Science, MSc / PGDip

Visualising data for statistical thinking and data-driven decision-making

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Course Overview

The MSc in Applied Data Science is designed to provide appropriate training to students with a non-specialist background to enable them to enhance their future opportunities and play a key role in digital economy.

The programme will educate students to work with, visualise and understand data, encourage statistical thinking and develop data-driving decision-making. In addition, the programme provides the necessary foundation in Mathematics, Statistics and basic programming skills that are key to a systemic understanding of the complexity of data and its analysis. It also provides key skills in several topics in Computer Science, such as Data Visualisation and Machine Learning. This programme is aimed at students who have a degree in any non-highly numerate subject, but who are interested in learning essential data science methods with various applications.

Please note, Applied Data Science, MSc, is appropriate for those who do not have an undergraduate degree in the Mathematics field (or equivalent).  If you have an undergraduate degree in Computer Science (or equivalent) and wish to pursue a data science route within your Masters, please see Data Science, MSc.

Why Applied Data Science at Swansea?

  • Top 201-250 in the World in Computer Science & Information Systems (QS World University Rankings by Subject 2025)
  • World-class facilities for mathematical and computational sciences
  • 100% of publications are world-leading and internationally excellent - Research Excellence Framework (REF) 2021

Your Applied Data Science Experience

In the first part of the course, you will begin your studies with mathematical and computational foundations of data science. This is followed by more advanced topics such as Machine Learning, Data Visualisation and Big Data. The programme will also include a final project that will focus on applications of the knowledge and skills in data science. Where possible, project topics will be tailored to students’ interests.

Over the course of your studies, you will be assessed by a combination of written examinations, coursework and the dissertation.

Your studies will be supported by facilities including the main university library - containing an extensive collection of mathematics resources - and Digital Services.

Also available to you is the 1300 sq. ft. Reading Room in the centre of the department. This is home to the departmental library and a suite of computers.

Our staff are experts in their fields with the majority being recognized by the Higher Education Academy with a Fellowship or Senior Fellowship.

  • Our Mathematics and Computer Science Departments are right next to the beautiful Swansea Bay beachfront, with numerous social and sport opportunities.
  • The £32.5M Computational Foundry building at our Bay Campus gives students access to bespoke study and teaching spaces designed by and for mathematicians.

Applied Data Science Employment Opportunities

Completing this MSc considerably enhances your data science-related career prospects, such as working as a data analyst, researcher, business analyst and statistician. Recent Swansea graduates have been employed by Admiral, Veramed, AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government.

Modules

The programme will contain 60 credits of Mathematics modules, which will provide a strong foundation in data analysis. In particular, these modules will involve foundation level Calculus, Linear Algebra, Probability and Statistics and Modelling. Basic programming skills and languages of direct relevance to Data Science will form an integral part of many of these modules.

There will also be 60 credits of relevant modules in Computer Science, such as Data Visualisation and Big Data. These will further enhance knowledge in data analysis. The programme will also include a 60-credit final project that will focus on applications of the knowledge and skills in data science. Where possible, project topics will be tailored to students’ interests.