Data Science

You are viewing this course for September start 2024

Data Science is a rapidly growing interdisciplinary area, with applications in business, government, public health, and the sciences. Its applications range from identifying customers’ buying patterns and monitoring machinery to tracking the spread of a disease and logging and improving an individual's health. There is therefore a huge unfilled demand for graduates with skills in ‘Big Data’.

Typical Entry Requirements

Entry Requirements 2:2 Bachelors (Honours) degree, or equivalent, in any discipline.  Non-graduates will be considered individually based on relevant work experience.

English Language Requirements IELTS 6.0 with minimum 5.5 in each component, or equivalent

Other Requirements Applicants are encouraged to submit an up-to-date CV as part of their application.

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Course Overview

Why study MSc Data Science at Aberystwyth University?

  • Aberystwyth University is a top 50 university for research power and intensity – REF 2014
  • Opportunity to study in Departments with links to many major companies and a strong research focus
  • Opportunity for graduates of any discipline to significantly enhance their employability
  • Opportunity to apply the knowledge from this course to other areas, including your initial undergraduate discipline
  • 100% of the Department of Computer Science’s research was deemed either world-leading or internationally excellent in terms of research impact – REF 2014
  • 98% of the Department of Computer Science’s research, and 100% of the Department of Mathematical Sciences’ research was of an internationally recognised standard or higher – REF 2014
  • Aberystwyth Department of Computer Science graduates exceed the national subject area average for employability
  • Our taught masters degrees are designed to meet the needs both of students intending a career in research, and those who want to accelerate an industrial career

Modules September start - 2024

Please note: The modules listed below are those currently intended for delivery during the next academic year and may be subject to change. They are included here to give an indication of how the course is structured.


Module Name Module Code Credit Value
Advanced Data Analytics CSM6720 20
Machine Learning for Intelligent Systems CSM6420 20
Modelling, Managing and Securing Data CSM3120 20
Statistical Concepts, Methods and Tools MAM5120 20
Statistical Techniques for Computational Scientists MAM5220 20


Module Name Module Code Credit Value
Fundamentals of Intelligent Systems CSM6120 20
Programming for Scientists CSM0120 20
Dissertation CSM9060 60

* Also available partially or entirely through the medium of Welsh


The range of careers to which our graduates advance is vast and continuously expanding. Examples of pathways our previous graduates have taken include working for/ as:

  • Google
  • MarkLogic
  • Investment banks 
  • Product Managers 
  • setting up their own companies
  • Developing careers in research 

There are many opportunities for Data Scientists in the jobs market, and whatever your intention post-MSc, you will be offered support with your career planning. 


Throughout this course, students will develop skills, qualities, and expertise that will make them extremely marketable to employers. On this course you will: 

  • Develop specialized technical skills in the areas of data handling, data management, data analytics and data mining, relational modelling, cryptography, and system security 
  • Develop subject-specific expertise, including an awareness of the legal, social, ethical and professional issues involved in handling data, and knowledge of statistical techniques and methods for large data sets 
  • Develop study and research skills 
  • Enhance your problem solving and analytical abilities 
  • Enhance your communication skills through a diverse mixture of learning and assessment methods 

University Careers Service 

Nationwide employers in the industry of Computer Science visit the university’s Careers Fairs. The university’s Careers Service also offers a wide variety of specialist services.

Teaching & Learning

How will I be taught?

 This course can be taken as a full-time one year course and can also be taken part-time. When taken full time, the course is divided over three semesters. 

During the first two semesters (September to May) students complete 120 taught credits. The third semester (June to September) is given over to the MSc project and dissertation (60 credits). Contact time for this course is approximately 12 hours a week in the first two semesters. 

During semester three, you will arrange your level of contact time with your assigned supervisor. The taught part of the course is delivered through lectures, student seminars and practical exercises. 

What will I learn? 

In the first two semesters you will undertake a number of core modules. These module include: 

  •  Machine Learning for Intelligent Systems

How will I be assessed? 

Assessment is a mix of written assignments, programming assignments, practical portfolios, practical examinations and written examinations. The successful submission of your research dissertation in semester three leads to the award of an MSc.