Curious about studying MSc Artificial Intelligence and Data Scienceat Swansea University? We've gathered all the key details—entry requirements, modules, fees, and more. Hear from real students by checking out reviews, or take the next step by booking an open day to explore it for yourself.
MSc - Master of Science
Bay Campus 1
Part Time
Sep 2027
2 Year
The MSc in Data Science gives you a solid grounding in data science concepts and technologies for extracting information and constructing knowledge from data. This course focuses on three core technical themes of data mining, machine learning, and visualisation. You study computational principles, methods, and systems for a variety of real-world applications that require mathematical foundations, programming skills, critical thinking, and ingenuity. Completing this MSc considerably enhances your data science career prospects. Our graduates often progress to rewarding employment within esteemed organisations. Below are a number of their recent destinations:Workflow developer, Irwin Mitchell, Programmer, Evil Twin Artworks, Web developer & web support, VSI Thinking, Software developer, Wireless Innovations , Associate business application analyst, CDC SoftwareSoftware developer, OpenBet Technologies.
This module will provide students with the opportunity of exploring a particular topic in computer science in some considerable depth. It is only open to students studying MSc Computer Science, MSc Advanced Computer Science, MSc Advanced Software Technology, MSc in High Performance and Scientific Computing, and MSc Data Science.
This module will introduce students to some fundamental research methodologies and good practice in research. They will undertake background research including a literature review and specify the aims of their MSc project.
Visual analytics is a human-centred area of computing that studies systems to support exploration and explanation of features in data sets. The course will provide an introduction to visual analytics and supporting necessary concepts in information visualisation. Visual analytics is the combination of visualisation and data analytics, which includes machine learning, to create effective data analysis systems.
This module introduces students to the fundamental topics of data mining, including data pre-processing techniques, applied probability and statistics, data mining algorithms (incl. associate rule, classification, clustering, outlier detection and probabilistic graphical model), and big data frameworks.
This module will discuss in-depth some of the most widely used and state-of-the-art artificial intelligence and machine learning techniques and their applications to big data problems. The students will gain both theoretical understanding of learning and practical know-how in applying those theories to real world problems. Topics include big data concept, data mining, learning theories, supervised and unsupervised learning, and reinforcement learning.
This course is an introductory course to the mathematical methods needed by a data scientist. It covers the basics of algebra, optimisation techniques, statistics, and Fourier analysis. The main goal of the class is for students to gain practical experience of the mathematical methods and tools that are essential in data science and that will be used in the other modules of this programme. The module is aimed at students with basic experience in mathematics.
4.4Located on the stunning Swansea Bay coastline, this Welsh university provides easy access to the city centre, as well as...
