Program Overview

Data Science

Key Facts

• UCAS Tariff: 120 - 104
• Course duration: 3 years
• Available for September start 2025

Course Overview

The BSc Data Science degree at Aberystwyth University combines mathematical, statistical, and computational approaches to equip you with the essential skills you will need to make sense of large amounts of data and forge a successful career in this arena.

Data science is entrenched in many aspects of modern society, and as the world generates increasing amounts of information about scientific research or our online shopping habits and social media usage, there is a rapidly growing global demand for people who can analyse and interpret such ‘Big’ Data. Data science is a stimulating area of study with strong employability prospects in a field which is currently experiencing a shortage of suitably qualified graduates.

Experts from our Departments of Mathematics and Computer Science will train you in programming and database design, data modelling, probability and estimation, statistical techniques and methods for testing software systems. A wide range of optional modules throughout the course enables you to focus your interests in particular areas or maintain a breadth of study. On graduation you will be well-positioned for a career in a range of industries which demand quantitative analysis or to pursue further study.

Why study Data Science at Aberystwyth?

• This course is taught jointly by the Department of Computer Science and the Department of Mathematics. Mathematics has been taught at Aberystwyth University since 1872, making the university the first in Wales to teach this subject. Our established heritage alongside our strong research based teaching ensures an innovative and stimulating experience.
• The combination of the modules delivered by the Department of Computer Science and the Department of Mathematics will give you a strong grounding in the underlying theory of Data Science as well as the practical skills to be able to apply that theory in real world data analytics.
• Upon successful completion of this degree, you will be able to design and carry out analysis of large sets of data and can draw implications from the results. This course will allow you to understand how data collected by companies can have a large effect on their operations.

Modules

Year 1

• Algebra (MA10510, 10 credits)
• Calculus (MP10610, 10 credits)
• Further Algebra and Calculus (MP11010, 10 credits)
• Introduction to Computer Infrastructure (CS10220, 20 credits)
• Introduction to Programming (CS12020, 20 credits)
• Mathematical Analysis (MA11110, 10 credits)
• Probability (MA10310, 10 credits)
• Programming Using an Object-Oriented Language (CS12320, 20 credits)
• Statistics (MA11310, 10 credits)

Year 2

• Algorithm Design and Data Structures (CS21120, 20 credits)
• Applied Statistics (MA26620, 20 credits)
• Distributions and Estimation (MA26010, 10 credits)
• Introduction to Numerical Analysis and its applications (MA25220, 20 credits)
• Linear Algebra (MA21410, 10 credits)
• Modelling Persistent Data (CS27020, 20 credits)
• Software Engineering (CS22120, 20 credits)

Year 3

• Machine Learning (CS36220, 20 credits)
• Minor Project (CS39620, 20 credits)
• Statistical Inference and Linear Models (MA36820, 20 credits)
• Linear Statistical Models (MA36510, 10 credits)
• Major Project (CS39440, 40 credits)

Options

• Comparative Statistical Inference (MA36010, 10 credits)
• Graphs and Networks (MA32410, 10 credits)
• Probability and Stochastic Processes (MA37410, 10 credits)
• Stochastic Models in Finance (MA37810, 10 credits)
• Topics in Biological Statistics (MA35210, 10 credits)

Careers

Career Prospects

There is a shortage of skilled Data Scientists, which means that graduates in this area are in demand! One study estimates that around 200,000 Data Scientists will be needed in the future.

Forbes Magazine labelled Data Scientist as “the sexiest job of the 21st century.”

The role of Data Scientist is finding and interpreting patterns in big data, and needs an excellent understanding of statistics and good computing skills.

Our graduates have found employment with employers such as:

• IBM
• HP
• Gloversure
• Plymouth Marine Laboratories
• CERN
• Walt Disney
• GCHQ

Transferable skills:

Throughout the course, you will improve and develop your:

• Group activities
• Communication skills
• Good time management
• Creative thinking

Teaching & Learning

What will I learn?

• In the first year, you will combine modules in programming and software with fundamental mathematics and statistics.
• In the second year you will extend your knowledge of statistics alongside data analysis and databases.
• In the final year you will bring your study together in a major individual project, covering a realistic data analysis problem, in addition to core and elective modules in statistics and computing.

How will I be taught?

• You will be taught by enthusiastic staff through a complementary set of teaching and learning methods and approaches, ranging from formal lectures, seminars and tutorials to practicals and individual and group-based project work.
• You will be assessed through a combination of coursework, practicals, projects, workshops and examinations.
• You will be assigned a personal tutor throughout your degree course, who will help you with any problems or queries, whether these are academic-related or personal issues. You should feel free to contact them at any time for help and advice.

Typical Entry Requirements

• UCAS Tariff: 120 - 104
• A Levels: BBB-BCC to include B in Mathematics
• GCSE requirements (minimum grade C/4): English or Welsh and Mathematics
• BTEC National Diploma: DDM-DMM with B in A level Mathematics
• International Baccalaureate: 30-28 with 5 points in Mathematics at Higher Level
• European Baccalaureate: 75%-65% overall with 7 in Mathematics
• English Language Requirements: See our Undergraduate English Language Requirements for this course. Pre-sessional English Programmes are also available for students who do not meet our English Language Requirements.

Useful Links

• Accommodation
• Advice for International Students
• English Language Requirements
• Fees & Finance
• Global Opportunities
• Online Resources Hub

Data Science at Aberystwyth University

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