University of Glasgow - Open Day
18 Jun 2026, 08:00
Glasgow

This programme explores the mathematical and statistical foundations of machine learning and artificial intelligence, equipping you with theoretical depth and practical skills to innovate in data-driven technologies
Why study this course at the University of Glasgow
This BSc combines expertise in Computing Science and Mathematics & Statistics, and offers a learning environment where theory meets real-world application with world-class research links, including the Alan Turing Institute. You’ll gain a deep understanding of AI fundamentals while exploring how they apply across areas like health, business, and finance, alongside ethical and societal considerations. It’s a programme designed to help you think critically, innovate, and make an impact in a rapidly evolving field.
Programme Structure
Year 1
You will choose between two pathways depending on prior programming experience. All students study Computing Science (40 credits), Mathematics (40 credits), and are recommended to take Statistics (40 credits), building a strong foundation for advanced study.
Year 2
You will deepen your understanding of core topics including algorithms, data structures, calculus, linear algebra, and statistical inference. Programming and mathematical modelling are integrated into coursework.
Years 3, 4 and 5
If you progress to Honours (years 3 and 4), study will focus on advanced machine learning, deep learning, optimisation, and statistical modelling. You will engage in independent research, ethical AI discussions, and interdisciplinary applications in fields like health, finance, and robotics.
If you are studying for the MSci, in years 4 and 5 you will 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.
Career Prospects
Graduates from this programme are well-prepared for careers in AI, data science, finance, healthcare, and academia. Employers include PwC, Deloitte, RBS, and tech firms.
The following entry points are available for this course:
Discover what it's like to study MSci in Machine Learning, Mathematics and Statistics at University of Glasgow: insights on the course, making friends, personal statement tips, uni prep, and recommended books, podcasts, and videos.
Find out more about qualification requirements for this course.
| Test | Grade | Additional details |
|---|---|---|
| IELTS (Academic) | 6.5 | 6.5 with no subtests under 6. We accept IELTS One Skill Retake. Tests must have been taken within 2.5 years of start date. Applicants must meet the overall and subtest requirements with a single test. |
| TOEFL (iBT) | 90 | 90 overall with Reading 20; Listening 19; Speaking 19; Writing 21. Tests must have been taken within 2.5 years of start date. Applicants must meet the overall and subtest requirements. |
| PTE Academic | 59 | 59 with minimum 59 in all subtests. Tests must have been taken within 2.5 years of start date. Applicants must meet the overall and subtest requirements using a single test. |
| Cambridge English Proficiency | 176 overall, no subtest less than 169. Tests must have been taken within 2.5 year sof start date. Applicants must meet the overall and subtest requirements using a single test. | |
| Cambridge English Advanced | 176 overall, no subtest less than 169. Tests must have been taken within 2.5 year sof start date. Applicants must meet the overall and subtest requirements using a single test. |
Full details of our English language requirements including which school qualifications we accept can be found on our website: https://www.gla.ac.uk/international/englishlanguage/requirements/
This section shows the range of grades students (with UK A-Levels or Pearson BTEC Level 3 National Extended Diplomas) who received offers were previously accepted with (learn more). It is designed to support your research but does not guarantee whether you will or won't get a place. Admissions teams consider various factors, including interviews, subject requirements, and entrance tests. Check all course entry requirements for eligibility.
We are unable to show previous accepted grades for this course. This could be because the course is new, it's a postgraduate course, there isn't enough historical data, or the provider has opted out of sharing their entry grades data for this course - learn more.
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website.
No additional fees or cost information has been supplied for this course, please contact the provider directly.
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