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Mathematics and Computer Science for Artificial Intelligence
Develop powerful analytical and problem-solving skills for leading roles in AI, data science and modern tech.
Course key facts
Qualification
BEng
Duration
3 years
Start date
October 2027
UCAS course code
GG02
Study mode
Full-time
Delivered by
Location
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South Kensington
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White City
-
Minimum entry standard
A*A*A (A-level)
41 points (International Baccalaureate)
Course overview
Study the fundamental mathematical theory and engineering practice that underpin Machine Learning and Artificial Intelligence. By combining the programming and algorithm skills of a computer scientist with the analysis and statistics understanding of a mathematician, you will be equipped for a career or further study in many of the most active and promising fields now and into the future.
The combination of mathematics and computing you will study will equip you with a fundamental understanding of the quantitative processes that underpin artificial intelligence and machine learning, preparing you for a leading role in the technologies that are revolutionising society.
You will develop professional software engineering skills honed by working on projects of increasing sophistication, enabling you to apply your theoretical understanding in our computer-powered society.
In later years of the programme, you will choose from scores of electives spanning higher mathematics and advanced computer science, enabling you to specialise in your choice of fields across these disciplines.
As a mathematics and computer science graduate, you will have access to careers and further study demanding either one of these degrees. Further, your skills will surpass those of single subject graduates in areas such as modelling, quantitative analysis, and data science where the two fields intersect.
Subject to university approval.
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Undergraduate events
Want to get a feel for life at Imperial?
Save the date for our next Open Days on 24–25 June and 12 September 2026. You can also find upcoming in-person and online events across the UK and overseas on our Events pages.
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This page is updated regularly to reflect the latest version of the curriculum. However, this information is subject to change.
Find out more about potential course changes.
Please note: it may not always be possible to take specific combinations of modules due to timetabling conflicts. For confirmation, please check with the relevant department.
The first year will provide you with the programming, computing and mathematical foundations needed for the course in later years.
You will study nine Core modules.
Core modules
In this module you will have the opportunity to develop your practical programming skills. This module will also give you a chance to put into practice some of the theoretical material covered in the first year lecture courses.
This module provides a transition towards the way you will be thinking about, and doing, Mathematics during your degree. It will stress the importance of precise definitions and rigorous proofs, but also discuss their relationship to more informal styles of reasoning which are often encountered in applications of Mathematics. Topics to be covered will include an introduction to elementary set theory, common proof strategies as well as common functions.
In this module you will have the opportunity to further your understanding of first-order logic, following on from the content of Introduction to University Mathematics. This module will cover various semantic methods for proving validity of arguments and logical equivalences. You will learn about several proof systems for first-order logic, and then apply these to reasoning about programs. You will see how Inductive Reasoning can be applied to reasoning about recursive programs, and how we can approach reasoning about imperative programs involving mutable state and loops. Finally, you will see how we can use precise logical specifications to help develop programs implementing some famous algorithms.
Analysis is a rigorous treatment of some basic concepts involving limits of real and complex numbers. It covers limits of sequences and series of real and complex numbers, the continuity and differentiability of functions, and limiting constructions leading to the integral of a single-variable function.
This module provides an introduction to applied mathematics. The goal is to provide you with a selection of mathematical tools and enable you to acquire the necessary skills to solve more complex problems in applied mathematics than you will have tackled previously.
Linear algebra is fundamental in mathematics. In this module you will generalise what you already know about systems of linear equations and matrices and view them in the more abstract, and more geometric, framework of vector spaces and linear transformations. The module also provides an introduction to group theory, another fundamental topic in abstract algebra.
In this module you will have the opportunity to learn about graph and tree structures, and a number of algorithms that operate over them. You will learn how to prove mathematical properties of graphs, how to design algorithms for sorting, searching and other common tasks, as well as various methods for determining the complexity of such algorithms. You will also learn about the P and NP complexity classes, and the concept of NP-completeness.
This module provides a self-contained introduction to probability and statistics. It will begin by translating intuitive concepts of probability into a formal axiomatic framework. Random variables will be introduced, and their properties relevant to statistical work will be discussed, formally and by computer simulation. Principles of statistics will be introduced, with a view toward practical statistical modelling. Using data sets from varied scientific contexts, you will fit and criticize statistical models with statistical packages such as R.
In this module you will have the opportunity to develop various practical skills in the context of machine learning, including programming, basic academic research and both written and oral communication skills, all of which are important attributes of a professional machine learning engineer. The programming aspects of this module will also give you a chance to put into practice some of the theoretical material covered in the first year lecture courses and to explore additional topics in computing that will be built on in later years.
In the second year you will learn the principles of engineering large systems and choose your mathematical specialisms.
You will study eight Core and Compulsory modules.
In the Spring term, you will choose a selection of optional modules from those listed below, providing a mixture of Computing and Mathematics options.
You must select one module from Group A, plus two modules from Group B.
Please note: The optional module lists may change subject to ongoing curriculum review and staffing constraints.
Core and Compulsory modules
- Practical Systems Engineering
- Computer Systems
- Software Engineering
- Machine Learning
- Real Analysis and Topology
- Multivariable Calculus
- Linear Algebra
- Designing for Real People
Optional modules – Group A (Computing)
- Systems for Machine Learning
- Software Verification
Optional modules – Group B (Mathematics)
- Groups and Rings
- Lebesgue Measure and Integration
- Differential Equations
- Partial Differential Equations in Action
- Statistical Modelling
The third year gives you more choice about what you learn, with the modules in this year at the leading-edge of industry practices.
You will study one module from the I-Explore catalogue.
You will also choose a selection of optional modules from those listed below, providing a mixture of Computing and Mathematics options.
You may select a maximum of two modules (not previously taken) from Group A and Group B.
You must select a minimum of four modules from Group A and Group C, plus a minimum of three modules from Group B and Group D. The Computing Group project modules counts as two normal modules.
Please note: the optional module lists may change subject to ongoing curriculum review and staffing constraints.
Compulsory modules
- I-Explore
Through I-Explore, you'll have the chance to deepen your knowledge in a brand new subject area, chosen from a huge range of for-credit modules.
All of our undergraduate courses include one module from I-Explore's wide selection. The module you choose will be fully integrated into your course's curriculum and count as credit towards your degree.
Optional modules – Group A (Computing)
- Systems for Machine Learning
- Software Verification
Optional modules – Group B (Mathematics)
- Machine Learning
- Groups and Rings
- Lebesgue Measure and Integration
- Partial Differential Equations in Action
- Statistical Modelling
- Differential Equations
- Classical Mechanics
- Complex Analysis
Optional modules – Group C (Computing)
- Advanced Computer Architecture
- Communicating Computer Science in Schools
- Graphics
- Computer Vision
- The Theory and Practice of Concurrent Programming
- Custom Computing
- Logic-Based Learning
- Network and Web Security
- Operations Research
- System Performance Engineering
- Robotics
- Software Engineering Group Project
- Type Systems for Programming Languages
- Computing Individual Project BEng
- Data Processing System
- Networked Systems
- Computing Research Collective
- Computational Optimisation
- Deep Learning
- Natural Language Processing
- Reinforcement Learning
- Databases
- Computer Networks and Distributed Systems
- Statistical Information Theory
Optional modules – Group D (Mathematics)
- Fluid Dynamics 1
- Fluid Dynamics 2
- Asymptotic Methods
- Optimisation
- Applied Complex Analysis
- Dynamics of Learning and Iterated Games
- Dynamical Systems
- Bifurcation Theory
- Geometric Mechanics
- Mathematical Finance: An Introduction to Option Pricing
- Mathematical Biology
- Quantum Mechanics 1
- Special Relativity and Electromagnetism
- Tensor Calculus and General Relativity
- Quantum Mechanics 2
- Theory of Partial Differential Equations
- Function Spaces and Applications
- Advanced Topics in Partial Differential Equations
- Finite Elements: Numerical Analysis and Implementation
- Computational Dynamical Systems
- Computational Linear Algebra
- Computational Partial Differential Equations
- Probability Theory
- Functional Analysis
- Fourier Analysis and Theory of Distributions
- Markov Processes
- Geometry of Curves and Surfaces
- Algebraic Curves
- Algebraic Topology
- Algebra 3
- Group Theory
- Galois Theory
- Graph Theory
- Group Representation Theory
- Formalising Mathematics
- Number Theory
- Algebraic Number Theory
- Statistical Theory
- Applied Statistical Inference
- Applied Probability
- Time Series Analysis
- Stochastic Simulation
- Survival Models
- Maths Individual Project BEng
- Stochastic Differential Equations in Financial Modelling
- Mathematical Logic
- Mathematical Biology 2: Systems Biology
- Rough Paths and Applications to Machine Learning
- Spatial Statistics
- Geometric Complex Analysis
- Introduction to Game Theory
- The Mathematics of Business and Economics
- Statistical Mechanics
To qualify for the award of a BEng on the Mathematics and Computer Science for Artificial Intelligence programme you must have met the following conditions:
- Passed Machine Learning
- Passed at least two other approved AIML modules
- At least two approved AI/ML modules to be at FHEQ Level 6
Approved AIML modules
- Machine Learning
- Systems for Machine Learning
- Statistical Modelling
- Logic-Based Learning
- Computational Optimisation
- Deep Learning
- Natural Language Processing
- Reinforcement Learning
- Optimisation
- Dynamics of Learning and Iterated games
- Markov Processes
- Statistical Theory
- Applied Statistical Inference
- Applied Probability
- Time Series Analysis
- Stochastic Simulation
- Rough Paths and Applications to Machine Learning
- Introduction to Game Theory
Teaching and assessment
Balance of teaching and learning
This is a general guide to how teaching and learning are usually balanced across this course. The methods used may change based on the modules you take.
Key
- Mathematics
- Computing
- Flexible Choice
Years 1
- 50% Title 1 goes here
- 50% Title 2 goes here
Year 2
- 50% Title 1 goes here
- 50% Title 2 goes here
Year 3
- 33% Title 1 goes here
- 33% Title 2 goes here
- 34% Title 3 goes here
Teaching and learning methods
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Lectures
-
Tutorials
-
Programming laboratories
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In-class problem solving
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Supervised project work
Balance of assessment
This is an example of how assessments are usually divided, based on a typical pathway through the course. The actual breakdown may vary depending on the modules you choose.
Key
- Coursework
- Practical
- Exams
Year 1
- 13% Title 1 goes here
- 33% Title 2 goes here
- 54% Title 3 goes here
Year 2
- 15% Title 1 goes here
- 25% Title 2 goes here
- 60% Title 3 goes here
Year 3
- 21% Title 1 goes here
- 18% Title 2 goes here
- 61% Title 3 goes here
Assessment methods
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Programming and written coursework
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Written and computer-based examinations
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Industrial software review techniques
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Group work
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Research reports
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Oral presentations
Entry requirements
We consider all applicants on an individual basis, welcoming students from all over the world.
How to apply
Apply via UCAS
Once applications open, you can register and start your application via the UCAS Hub. There, you can add this course as one of your choices and track your application.
Applications open on 12 May 2026.
Admissions test (TMUA)
To be eligible for selection for this course for 2027 entry, you must sit the Test of Mathematics for University Admission (TMUA) as part of the application process.
Check the entry requirements section on this page to learn more about the TMUA and how to register for this test.
Assessing your application
Admissions Tutors consider all the evidence available during our rigorous selection process and the College flags key information providing assessors with a more complete picture of the educational and social circumstances relevant to the applicant. Some applicants may be set lower offers and some more challenging ones.
Interviews are not standard but may be offered to some candidates at the discretion of the admissions tutors.
An ATAS certificate is not required for students applying for this course.
Transfers from the single subject Computing or Mathematics courses to any of the joint Mathematics and Computer Science courses are normally not possible but are dealt with on a case-by-case basis.
Transfer between the BEng in Mathematics and Computer Science and MEng in Mathematics and Computer Science courses is possible until the end of Year 3, subject to meeting certain minimum results criteria if transferring onto an MEng course.
Transfer between the AI specialism Mathematics and Computer Science courses and non-specialist Mathematics and Computer Science courses is possible until the end of the course, subject to meeting certain elective module restrictions.
If you are an international student, transferring to a different course could have an impact on your student visa.
Please visit the Department of Computing and Department of Mathematics for further information.
Fees and funding
Home fee
2027 entry
£10,050* per year
Fee to be confirmed
*Home tuition fees
In England and Wales, the UK government sets the maximum tuition fee (known as a 'fee cap') chargeable by universities for Home students. Imperial’s Home fees for undergraduate courses starting in 2027 will align with this cap, which means that, subject to parliamentary approval, they are expected to be £10,050.
It is current Imperial policy to charge Home fees in line with the Government’s fee cap. The UK government announced its proposed fee caps for the 2026–27 and 2027–28 academic years in November 2025.
The fee cap beyond this hasn’t been announced yet but the Government plans to increase the fee cap each year to match inflation.
So, you should expect a rise in your fee each year. As soon as we know what this will be for 2028- to 2029 academic year and beyond, we will publish it on our course pages.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
If you're a Home student, you can apply for a Tuition Fee Loan from the UK government to cover the entire cost of tuition for every year of your course.
The loan is paid directly to the university.
You will start repaying it only after you leave your course, have a job, and are earning above a certain amount.
Once the repayments start, the amount you pay each month depends on how much you earn, not on how much you owe in total.
Upcoming changes: Lifelong Learning Entitlement
From January 2027, students who live in England can access student finance through the Lifelong Learning Entitlement (LLE) – a single funding system that brings together Tuition Fee and Maintenance Loans.
The LLE currently applies to England only. Student finance in Wales, Scotland and Northern Ireland is not affected by this change.
You can learn more about the LLE on the GOV.UK website.
Home students can apply for a means-tested Maintenance Loan to help with their living costs.
How you apply for student finance depends on whether you have studied before and where you’re from or normally live. Find out more on the UK government's website.
Upcoming changes: Lifelong Learning Entitlement
From January 2027, students who live in England can access student finance through the Lifelong Learning Entitlement (LLE) – a single funding system that brings together Tuition Fee and Maintenance Loans.
The LLE currently applies to England only. Student finance in Wales, Scotland and Northern Ireland is not affected by this change.
You can learn more about the LLE on the GOV.UK website.
The Imperial Bursary is available to all Home undergraduate students with a household income below £70,000 per year.
The amount awarded is based on your household income, with up to £5,000/year available for students from the lowest income households.
It's money which you don't need to pay back, and it's paid on top of any government funding you may also receive.
It is available for each year of your course, as long as your annual household income remains below £70,000.
You might need to budget for additional costs related to your course that aren't covered by your tuition fees – like field trips, books and protective clothing.
Our extra costs page outlines the additional costs related to courses in each of our departments. It's not an exhaustive list and any additional costs you could incur will be determined by the course and modules you choose.
Overseas fee
2027 entry
Not set
As a guide, the Overseas fee for 2026-27 was £42,700.
Whether you pay the Home or Overseas fee depends on your fee status. This is assessed based on UK Government legislation and includes things like where you live and your nationality or residency status. Find out how we assess your fee status.
You might need to budget for additional costs related to your course that aren't covered by your tuition fees – like field trips, books and protective clothing.
Our extra costs page outlines the additional costs related to courses in each of our departments. It's not an exhaustive list and any additional costs you could incur will be determined by the course and modules you choose.
How will studying at Imperial help my career?
99% Of Imperial Computing graduates in work or further study*
- 99% Of Imperial Computing graduates in work or further study*
- 1%
94% Of Imperial Computing graduates in highly skilled work or further study*
- 94% Of Imperial Computing graduates in highly skilled work or further study*
- 6%
*2022-23 graduate outcomes data, published by HESA in 2025
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Gain transferable skills relevant to a career in industry and academia.
With specialised knowledge, you'll be highly sought after in a range of sectors.
Management consultancy, corporations, computer gaming and special effects are just some of your options.
Other potential career paths could include banking and finance.
Further links
Contact the department
- Email: jmc-admissions@imperial.ac.uk
- Admissions director: Dr Marie-Amelie Lawn
- Course director: Dr Mark Wheelhouse
- Mathematics director: Professor David Ham
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Request info
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Course data
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You can find further information about your course, including degree classifications, regulations, progression and awards in the programme specification for your course.
Programme specifications