Machine Learning, Mathematics & Statistics BSc/MSci
Our programme is designed for students who want to delve deep into the mathematical and statistical foundations of machine learning, while also developing the computational skills to apply them. The programme emphasises rigorous training in probability, inference, optimisation, and statistical modelling. This training is integrated with hands-on experience of modern machine learning techniques.
The School of Computing Science and School of Mathematics & Statistics have a long-established culture of partnership. They combine internationally recognised strengths in algorithms, machine learning, mathematics and statistics. This collaboration underpins a research environment that spans natural language processing, neural networks, computer vision, robotics and data science. And connects Glasgow directly to the national innovation through membership of The Alan Turing Institute.
You will gain rigorous insight into the theory that powers artificial intelligence. This will include:
- linear algebra
- probability
- statistical inference
- optimisation
- machine learning
- deep learning
This ensures graduates not only apply AI methods, but also innovate at the algorithmic level. And contribute to the next generation of approaches and applications.
You will be encouraged to pursue cross-disciplinary applications in fields such as business, health and finance. While also engaging with the ethical, regulatory, and societal dimensions of AI.
Choosing Glasgow means studying in an environment where Computing Science and Mathematics & Statistics come together. To equip you with both the theoretical depth and the practical agility to address the most pressing technological and societal challenges of the future.
- September start
- Session dates
- Machine Learning, Mathematics & Statistics BSc: G500 4 year degree
- Machine Learning, Mathematics & Statistics MSci: G501 5 year degree
Programme structure
Year 1
At Level 1 we offer two pathways. So you can begin your degree at the right level for you. Pathway 1 is designed for students with prior programming experience. Pathway 2 is ideal if you are completely new to programming. In both cases, you will take 40 credits of Computing Science within your 120-credit year. All students also take 40 credits of Mathematics, and we recommend a further 40 credits of Statistics. This will provide a strong foundation for later study. Whichever pathway you choose, you will be fully prepared to progress to Honours level. If you decide after your first year that a different direction is right for you, it is often possible to switch into many of the other programmes offered within the School of Computing Science or the School of Mathematics and Statistics.
Pathway 1
- Computing Science 1P (Standard Route)
- Computing Science 1F - Computing Fundamentals
- Computing Science - 1S Systems
- Mathematics 1
- Statistics 1Y: Introduction to Statistics: Learning from Data
- Statistics 1Z: Data Modelling in Action
Pathway 2
- Computing Science 1PX (Alternate Route)
- Computing Science - 1S Systems
- Mathematics 1
- Computing Science - 1S Systems
- Statistics 1Y: Introduction to Statistics: Learning from Data
- Statistics 1Z: Data Modelling in Action
Year 2
Core courses
There are two pathways of courses currently offered at Level 2 for Standard Route students. Either pathway enables students to continue to Honours level. Both pathways have an additional progression route into Statistics at Honours level.
Pathway 1
- Artificial Intelligence 2X: Mathematics for Machine Learning
- Artificial Intelligence 2Y: Knowledge Representation and Decision Making
- Algorithmic Foundations 2
- Algorithms & Data Structures 2
- Mathematics 2A: Multivariable Calculus
- Mathematics 2B: Linear Algebra
- Statistics 2R: Probability
- Statistics 2X: Probability II
- Statistics 2S: Statistical Methods, Models and Computing 1
- Statistics 2Y: Statistical Methods, Models and Computing 2
Pathway 2
- Artificial Intelligence 2X: Mathematics for Machine Learning
- Artificial Intelligence 2Y: Knowledge Representation and Decision Making
- Algorithmic Foundations 2
- Algorithms & Data Structures 2
- Mathematics 2A: Multivariable Calculus
- Mathematics 2B: Linear Algebra
- Statistics 2R: Probability
- Statistics 2X: Probability II
- Statistics 2S: Statistical Methods, Models and Computing 1
- Statistics 2Y: Statistical Methods, Models and Computing 2
- Computing Science
Optional courses
Students are able to take 10/20 credits (depending on pathway) of relevant Level 1 and/or Level 2 courses.
Year 3
Core courses
- Artificial Intelligence: Machine Learning
- Artificial Intelligence: Deep Learning
- 4H: Theoretical Foundations of Machine Learning and Deep Learning
- Linear Models 3
- Generalised Linear Models
- Inference 3
- Bayesian Statistics
Optional courses
In Year 3, students will also choose 20 credits from the optional courses listed at Level 4 (SCQF 9) and Level 5 (SCQF 10) in the Mathematics & Statistics, and Computing Science course catalogues. Some options will require that you have studied certain subjects beforehand.
Year 4
Core courses (BSc)
- Science Individual Project
Core courses (MSci)
- Science Individual Project
- Research Methods And Techniques (M) for MSci
Optional courses
Students choose courses listed at Level 4 (SCQF 9) and Level 5 (SCQF 10) in the Mathematics & Statistics, and Computing Science course catalogues. Some options will require that you have studied certain subjects beforehand.
Year 5 (MSci only)
Core courses (MSci)
- Science Individual Research Project
- Project Research Readings In Computing Science (M)
Optional courses
Students in year 5 also choose courses listed at Level 4 (SCQF 9) and Level 5 (SCQF 10) in the Mathematics & Statistics, and Computing Science course catalogues. Some options will require that you have studied certain subjects beforehand.
Programme alteration or discontinuation
The University of Glasgow endeavours to run all programmes as advertised. In exceptional
circumstances, however, the University may withdraw or alter a programme. For more information,
please see: Student contract.
Entry requirements
for entry in 2026
Admissions guidance
English language
For applicants from non-English speaking countries, as defined by the UK Government, the University sets a minimum English Language proficiency level.
English language requirements
Career prospects
Graduates of this programme develop a rare combination of deep mathematical and statistical knowledge with practical machine learning skills. This expertise prepares you to take on roles where you can design new approaches, solve complex problems, and push the boundaries of how data is used. Such skills are in high demand across research, industry, and society, opening doors to a wide variety of careers and postgraduate opportunities.
Degrees and UCAS codes
When applying you will need to know the UCAS code for the subject or subject-combination that you wish to apply to:
BSc
MSci
Fees and funding
Tuition fees
How and when you pay tuition fees depends on where you’re from: see Tuition fees for details.
Scholarships
The University is committed to supporting students and rewarding academic excellence. That's why we've invested more than £1m in additional scholarship funding in recent years.
The scholarships above are relevant to this programme. For more funding opportunities search the scholarships database
How to apply
Full-time students must apply through the Universities & Colleges Admissions Service (UCAS).
SQA applicants who are eligible for our Widening Participation programmes are encouraged to participate in one or more of these programmes, including Summer School, to support your application and the transition to higher education.
International students to Arts, Engineering, Law, Nursing, Science, and Social Sciences can also apply using The Common Application: however, if applying to more than one UK university, we recommend using UCAS. Applications to Dentistry, Education, Medicine, and Veterinary Medicine must be made through UCAS.
Application deadlines
- 15 October: if including Dentistry, Medicine, Veterinary Medicine or also applying to Oxford or Cambridge
- 14 January: all other UK applicants (unless otherwise stated on the UCAS website)
- 30 June: international students.
We do not usually accept any applications after these deadlines.
It's your responsibility to ensure the accuracy of your application before submission. Requests to correct application content, change degree programme or change college of entry, will not be accepted after these deadlines. This policy is in place to ensure fairness and consistency to all applicants, and no exceptions will be made.
- Apply at www.ucas.com or through your school or college
- Contact UCAS on 0871 468 0468
- Apply at commonapp.org (international students to certain areas only)
How to apply for Advanced Entry
Apply for year 2 (Y2) on your UCAS application. If the specific subject is unavailable for Advanced Entry or your application for year 2 entry is unsuccessful, you will be automatically considered for year 1 entry. You do not have to submit a separate UCAS application.
Subject league tables
Times & Sunday Times Good University Guide [Computer Science]
Complete University Guide [Computer Science]
Guardian University Guide [Computer Science & Information Systems]
