Overview
Mathematics is at the centre of AI and machine learning. It uses statistics and probability to interpret data, identify trends, and make predictions. The AI market is booming. By 2031 the market share is estimated at £1.23tn ($1.68tn) (Statista Oct 2025).
There’s significant demand for AI and mathematics graduates who can code and understand the theory underpinning the systems they are building. Sectors such as technology, business, finance, engineering, robotics, research and the sciences all need these skills. You’ll develop the foundations needed to progress into roles involving data and statistics, research and machine learning.
Gain in-demand maths skills with an emphasis on AI
Get the theory, the quantitative skills, and the practical technological skills you need to solve real-world problems using AI. This maths and AI degree is for students who enjoy mathematics and want to understand how artificial intelligence works at a fundamental level. You’ll learn core skills in:
- Linear algebra: Essential for understanding data representation, neural networks, and dimensionality reduction.
- Probability and statistics: Crucial for machine learning models, Bayesian methods, and data analysis.
- Calculus and optimisation: The basis for training algorithms, such as gradient descent, and understanding how models learn.
- Programming: Essential for implementing and testing artificial intelligence algorithms. You’ll develop expertise in Python and R.
- AI for computer vision and natural language processing.
- Generative AI.
- Data Science: Essential for training and developing AI algorithms.
Get industry experience on a placement
As part of our mathematics and AI degree you can get hands-on experience on a three-month summer placement. It’s a great chance to put your classroom learning into practice. Placements with local SMEs as well as large corporate companies are offered to third year students.
In Year 3 you can take an optional professional development course. This equips you with the necessary skills to secure a placement.
Build connections with industry
You’ll engage with industry through guest lectures and local industry career events. Recent speakers include:
- Huawei
- Bigspark
- Red Star (AI for healthcare)
- Virtonomy
- KBC Group
- Leonardo UK
You’ll also experience work-related learning opportunities such as group projects and problem-based learning or simulations. We regularly engage with organisations such as:
- Accenture
- Diageo
- Honeywell
- JP Morgan
- Scottish Enterprise
- Scottish Water
Study abroad
Study abroad at universities across North America, Australia, and Europe. Experience what it’s like to learn in an international environment. Gain a fresh perspective on your studies, build your international network and enhance your career opportunities. Previous students have studied at:
- San Diego State University, USA
- University of Alabama, Birmingham, USA
- City University of Hong Kong
- Simon Fraser University, Canada
- Otto-Friedrich University Bamberg, Germany
Top reasons to study with us
Prizes or awards
Each year we offer the following prizes:
- Outstanding performance in 1st year Mathematics modules
- Outstanding performance in 2nd year Mathematics modules
- Two prizes of membership of the Institute of Mathematics and Its Applications for outstanding performance in mathematics degree programme
- The Francis K Bell prize for most improved student in 3rd year
- The Kate Howie award for best 4th year student in statistics modules
- A Faculty research prize for an outstanding research project
Entry requirements
Year 1 entry – Four-year honours
Highers
ABBB
A-levels
BBB
IB Diploma
28 points
BTEC (Level 3)
DDM
Essential subjects
Mathematics
Essential subjects must have been taken within the last five years to ensure your required subject knowledge is current. Recent work experience can be taken into consideration in place of a formal qualification.
Widening access students
Widening access students may be eligible for an adjusted offer of entry. To find out if this applies to you go to our widening access pages.
Care-experienced applicants will be guaranteed an offer of a place if they meet the minimum entry requirements.
Year 2 entry – Three-year honours
Advanced Highers
ABB
A-levels
ABB
IB Diploma
32 points
Essential subjects
Mathematics
Essential subjects must have been taken within the last five years to ensure your required subject knowledge is current. Recent work experience can be taken into consideration in place of a formal qualification.
Other Scottish qualifications
Scottish HNC/HND
Year one minimum entry - Bs in graded units.
Access courses
University of Stirling access course - for mature students only. You must pass the course with 50% or above.
SWAP Access course - for mature students only.
Email our Admissions Team for advice about other access courses.
Foundation Apprenticeships
Considered to be equivalent to 1 Higher at Grade B
Essential subjects
Mathematics
Essential subjects must have been taken within the last five years to ensure your required subject knowledge is current. Recent work experience can be taken into consideration in place of a formal qualification.
Other qualifications
English, Welsh and Northern Irish HNC/HND
Merits and Distinctions
English access course
Access to Higher Education Diploma - 60 credits with a minimum of 45 credits at level 3.
Essential subjects
Mathematics
Essential subjects must have been taken within the last five years to ensure your required subject knowledge is current. Recent work experience can be taken into consideration in place of a formal qualification.
International entry requirements
Advanced entry
Advanced entry may by possible depending on your qualifications.
Other routes of entry
If you don't currently meet our academic requirements, University of Stirling International Study Centre offers a variety of preparation programmes that can earn you the qualifications and skills you need to progress onto some of our courses. Explore University of Stirling International Study Centre to see the routes available.
English language requirements
If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS Academic or UKVI 6.0 with a minimum of 5.5 in each sub-skill.
- Pearson Test of English (Academic) 60 overall with a minimum of 59 in each sub-skill.
- TOEFL exams taken before 21 January 2026: 80 overall with 18 in reading, 17 in writing, 17 in listening, 20 in speaking.
- TOEFL exams taken from 21 January 2026: 4 overall with no less than 4 in any band.
See our information on English language requirements for more details on the language tests we accept and options to waive these requirements.
Pre-sessional English language courses
If you need to improve your English language skills before you enter this course, University of Stirling International Study Centre offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for entry to this degree.
Find out more about our pre-sessional English language courses
Course details
Mathematics learning covered at secondary level is reviewed and applied before being developed further. This ensures a smooth transition from a school teaching approach to a university one.
You’ll then continue with advanced modules in many different areas of mathematics and AI.
Modules
| Yr 1, semester 1 - Autumn | Introduction to Computing Science (CSCU9P1) | 20 credits |
| Yr 1, semester 1 - Autumn | Calculus 1 (MATU9N1) | 20 credits |
| Yr 1, semester 1 - Autumn | Discrete Structures (MATU9S1) | 20 credits |
| Yr 1, semester 2 - Spring | Introduction to Data Science (CSCU9S2) | 20 credits |
| Yr 1, semester 2 - Spring | Practical Statistics (MATU9D2) | 20 credits |
| Yr 1, semester 2 - Spring | Calculus II & Probability (MATU9N2) | 20 credits |
| Yr 2, semester 3 - Autumn | Database Principles and Applications (CSCU9B3) | 20 credits |
| Yr 2, semester 3 - Autumn | Professional Development for Computer Scientists (CSCU9CP) | 0 credits |
| Yr 2, semester 3 - Autumn | Scripting for Data Science (CSCU9M3) | 20 credits |
| Yr 2, semester 3 - Autumn | Vectors, Matrices, and Complex Numbers (MATU9A3) | 20 credits |
| Yr 2, semester 4 - Spring | NoSQL Databases and Data Warehousing (CSCU9B4) | 20 credits |
| Yr 2, semester 4 - Spring - Option Group | Optimisation: From Theory to Application (MATU9JC) | 20 credits |
| Yr 2, semester 4 - Spring - Option Group | Numerical Analysis (MATU9JD) | 20 credits |
| Yr 2, semester 4 - Spring | Linear Algebra (MATU9M4) | 20 credits |
| Yr 3, semester 5 - Autumn - Option | Professional Development for Computer Scientists (CSCU9CP) | 0 credits |
| Yr 3, semester 5 - Autumn | Introduction to Machine Learning (CSCU9M5) | 20 credits |
| Yr 3, semester 5 - Autumn - Option Group | Statistical Modelling (MATU9EG) | 20 credits |
| Yr 3, semester 5 - Autumn - Option Group | Statistical Inference (MATU9MB) | 20 credits |
| Yr 3, semester 5 - Autumn - Option Group | Time Series & Inverse Problems (MATU9MD) | 20 credits |
| Yr 3, semester 5 - Autumn - Option Group | Mathematical Modelling (MATU9ME) | 20 credits |
| Yr 3, semester 5 - Autumn | Mathematical Skills for Employment (MATU9GP) | 20 credits |
| Yr 3, semester 6 - Spring | Natural Language Processing and Computer Vision (CSCU9M6) | 20 credits |
| Yr 3, semester 6 - Spring - Option | Computing Science Industrial Summer Placement (CSCU9SP) | 10 credits |
| Yr 3, semester 6 - Spring - Option Group 1 | Optimisation: From Theory to Application (MATU9JC) | 20 credits |
| Yr 3, semester 6 - Spring - Spring - Option Group 1 | Numerical Analysis (MATU9JD) | 20 credits |
| Yr 3, semester 6 - Spring - Option Group 2 | Statistical Modelling (MATU9EG) | 20 credits |
| Yr 3, semester 6 - Spring - Option Group 2 | Statistical Inference (MATU9MB) | 20 credits |
| Yr 3, semester 6 - Spring - Option Group 2 | Time Series & Inverse Problems (MATU9MD) | 20 credits |
| Yr 3, semester 6 - Spring - Option Group 2 | Mathematical Modelling (MATU9ME) | 20 credits |
| Yr 4, semester 7 - Autumn | Data Science Applications (CSCU9DA) | 20 credits |
| Yr 4, semester 7 - Autumn - Option Group | Statistical Modelling (MATU9EG) | 20 credits |
| Yr 4, semester 7 - Autumn - Option Group | Statistical Inference (MATU9MB) | 20 credits |
| Yr 4, semester 7 - Autumn - Option Group | Time Series & Inverse Problems (MATU9MD) | 20 credits |
| Yr 4, semester 7 - Autumn - Option Group | Mathematical Modelling (MATU9ME) | 20 credits |
| Yr 4, semester 7 - Autumn | Advanced Optimisation and Artificial Intelligence (MATU9AI) module details not yet available | 20 credits |
| Yr 4, semester 8 - Spring - Option Group | Statistical Modelling (MATU9EG) | 20 credits |
| Yr 4, semester 8 - Spring - Option Group | Statistical Inference (MATU9MB) | 20 credits |
| Yr 4, semester 8 - Spring - Option Group | Time Series & Inverse Problems (MATU9MD) | 20 credits |
| Yr 4, semester 8 - Spring - Option Group | Mathematical Modelling (MATU9ME) | 20 credits |
| Yr 4, semester 8 - Spring | Research Dissertation (MATU9RD) | 40 credits |
Course details
Teaching
You will study mathematics and artificial intelligence at Stirling through a mixture of in-person lectures, seminars, and computer labs.
You'll be encouraged to develop as an independent learner, working through reading and tasks set on a weekly basis. You are expected to set aside a substantial part of your week to complete this work.
During seminar and lab sessions, you will discuss topics you have been given to prepare in advance, work through tasks in groups and can ask questions. Our learning and teaching approach helps you to have the confidence to learn independently while developing a wide range of skills.
Assessment
Additional weekly assignments are used by tutors and students to monitor progress. In some modules class tests are replaced by projects in which you’ll solve problems based on real-world data. Typically, in your final year you’ll undertake a challenging project or series of problems under the guidance of a project supervisor.
Study abroad
You can study abroad through our well-established connections with North American, Australian and European universities.
Fees and funding
Fees and costs
2027 fees are yet to be announced.
Additional costs
There are some instances where additional fees may apply. Depending on your chosen course, you may need to pay additional costs, for example for field trips. Learn more about additional fees.
Funding
See what funding opportunities and loans are available to help you with tuition and living costs.
Students from Scotland
Find funding opportunities for Scottish students.
Students from England, Wales, Northern Ireland and Republic of Ireland
Eligible students will receive our Stirling Success Scholarship which is worth £5,000.
International students
Eligible international students will automatically receive a scholarship worth between £10,000-£20,000 over the duration of your course. Find funding opportunities for international students.
Cost of living
If you’re domiciled in the UK, you can typically apply to your relevant funding body for help with living costs. This usually takes the form of student loans, grants or bursaries, and the amount awarded depends upon your personal circumstances and household income.
International (including EU) students won’t normally be able to claim living support through SAAS or other UK public funding bodies. You should contact the relevant authority in your country to find out if you’re eligible to receive support.
Payment options
We aim to be as flexible as possible, and offer a wide range of payment methods - including the option to pay fees by instalments. Learn more about how to pay.
After you graduate
There is a growing jobs market for graduates with skills in AI, data science and the mathematical ability to understand and verify output.
You'll graduate from our BSc (Hons) Mathematics and Artificial Intelligence with the computational skills to build systems and the mathematical acumen to innovate and research.
