Mathematics with Data Science and Artificial Intelligence BSc
3-4 years
In today’s data-driven world, there is a high-demand for professionals who can use, design and build tools for extracting and extrapolating knowledge from data. This degree will equip you with a mathematical foundation and the interdisciplinary skills needed for a successful career in data science and AI.
Start date:
Course information
Typical offer ABB
UCAS codes G120, G121
Institute code L34
Taught by School of Computing and Mathematical Sciences
Course description
Course description
Please note, this course is being advertised subject to approval.
Our Mathematics with Data Science and Artificial Intelligence BSc is interdisciplinary, combining traditional mathematical techniques with state-of-the-art applications in the field of data science and artificial intelligence (AI). It will provide you with a sound background in the techniques of mathematics and statistics, training in data science tools, computational and programming skills, as well as an understanding of data science practice.
You will gain expertise in handling large sets of data and drawing knowledge, patterns and trends from these data sets. This degree will cover machine learning and AI, statistical and mathematical modelling and teach a range of programming languages.
Your third year includes a research project on a data science/AI topic.
Development of data analysis and programming skills is an integral part of all our mathematics degrees. Through a combination of computer labs and dedicated modules, you will learn to use the computational functions in Excel, program in R, Python and Matlab and use LaTeX for scientific writing. No previous knowledge of computing is required for any of our degrees.
Entry requirements
Entry requirements
- A/AS-levels: ABB including Maths. Two AS-levels considered in place of one A-level.
- EPQ with A-levels: BBB + EPQ at grade B. A-level subjects to include Maths.
- Access to HE Diploma: Pass Diploma with a minimum of 45 credits at level 3, 30 of which must be at Distinction. Plus A-level Maths at grade A-B. We may consider substantial Level 3 Maths Access credits in place of A-level Maths. Please contact admissions regarding eligibility.
- International Baccalaureate: Pass Diploma with 30 points including grade 5 in HL Maths.
- BTEC Nationals: Pass Extended Diploma with DDM, plus grade B in A-level Maths. BTEC not accepted by itself. Please contact Admissions regarding eligibility.
Other official national and international qualifications considered from across the world. You can review some of the qualifications we accept on our countries page and English Language equivalencies.
If your qualification or country is not listed, please contact us for more information, including the name and result of the qualification you have studied.
Second year entry may be possible with suitable qualifications.
Contextual offers
The University of Leicester is committed to providing equitable opportunities for all applicants from all backgrounds. We make contextual offers to support students who may be impacted by the area they live in, their personal circumstances or who have completed one of our progression programmes. These offers are usually one or two grades lower than the standard entry requirements. To qualify for a contextual offer, you must apply for an eligible course and meet specific criteria – check if you’re eligible.
Selection process
When considering your application, we will look for evidence that you will be able to fulfil the objectives of the course and achieve the standards required. We will take into account a range of factors including previous exam results.
Applicants are not normally interviewed. If you receive an offer you will be invited to visit the School.
English Language Requirements
IELTS 6.0 or equivalent. If your first language is not English, you may need to provide evidence of your English language ability. If you do not yet meet our requirements, our English Language Teaching Unit (ELTU) offers a range of courses to help you to improve your English to the necessary standard.
International Qualifications
Find your country in this list to check equivalent qualifications, scholarships and additional requirements.
Countries ListFees and funding
Fees and funding
UK Students
Starting in 2026
- £9,535 in your first year. Tuition fees may increase in subsequent years in line with inflation, subject to government regulations. The inflation rate used will be the Retail Price Index excluding mortgage payments (RPIX)
- Year in Industry: your fee will be £1,905 for that year
Find out more about scholarships and funding.
Additional costs
- Please note that you will need to buy a Casio FX83GT calculator (approximately £6). This is not included in your tuition fee.
International Students
Starting in 2026
- £25,100 per year
- Year in Industry: £3,765 which is 15% of the full-time tuition fee
If you are resident outside the UK and the Republic of Ireland, you will need to pay a deposit of £3,000 to secure your place. This will be subtracted from your total tuition fee.
If you are an EU national with settled or pre-settled status under the EU settlement scheme, you may qualify for the UK fee (subject to criteria).
Find out more about scholarships and funding.
Additional costs
- Please note that you will need to buy a Casio FX83GT calculator (approximately £6). This is not included in your tuition fee.
Careers and employability
Careers and employability
This course will prepare you for a career as a data professional, with career opportunities such as:
- Machine Learning Engineer
- Data Engineer
- Software Architect
- Data Science Consultant
- Data Scientist
- Data Architect
- Database Administrator.
These roles are in high demand across a broad range of sectors including healthcare, engineering, finance and marketing.
This course will equip graduates with a sound background in mathematics and statistics, provide computational and programming skills as well as developing a solid grasp of machine learning and artificial intelligence tools and an understanding of data science practice.
Our mathematics graduates go on to excel in roles in industries such as finance and insurance, education, manufacturing trade and construction, information and communication, science and technology, public administration and civil service sectors, as well as undertaking further study.
Get career-ready at Leicester with guidance from our award-winning Careers and Employability Service. We're here to give you a lifetime offer of support, even after graduation. Our team of specialist careers advisers and mentors will help you every step of the way. From supporting you with CVs and interviews, to volunteering opportunities and placements, we're here to help you reach your professional goals.
Facilities
Facilities
You will have access to the Percy Gee Computer Laboratory, which offers individual and group workspaces for practical tutorial sessions, as well as independent study outside of timetabled activities. With your student ID card, you will have 24/7 access to our excellent teaching facilities, which are only available to students in the School of Computing and Mathematical Sciences. You can either work on a variety of Linux distributions available to you or start a virtual machine running Windows for your programming activities or other project work. A Student Study and Social Space is also available in the Ken Edwards Building, for a quiet study space.
The David Wilson Library Computer Laboratory is used for practical sessions, as well as tutorials and supports both individual and group work study. During taught sessions, the staff member delivering is able to display their session content on a TV at the end of each row of student PCs, to ensure that you can see what is going on from wherever you sit in the computer lab. Outside of timetabled sessions, you will be able to access and use this lab individually or together with a group of your peers.
Course structure
Year 1
Year 1
Modules
Semester 1
- Calculus and Analysis 1
- Linear Algebra 1
- Fundamentals of University Mathematics
- Programming Fundamentals
Semester 2
- Calculus and Analysis 2
- Linear Algebra 2
- Probability and Statistics
- Algorithms, Data Structures and Advanced Programming
Modules shown represent choices available to current students. The range of modules available and the content of any individual module may change in future years.
Year 2
Year 2
Modules
Semester 1
Core modules
Optional modules
Semester 2
Core modules
- Mathematical Foundations of AI and Machine Learning
- Statistical Data Analysis
- AI for Data Science
Semester 2
Optional modules
Modules shown represent choices available to current students. The range of modules available and the content of any individual module may change in future years.
Year in Industry (optional)
Year in Industry (optional)
If you want to, you can take a year out between Years 2 and 3 to work in an industrial placement (provided you meet set criteria). Or you can opt to continue studying at the University and complete your degree in three years.
NB. A year spent on an industrial placement still incurs a tuition fee, but this is much lower than for a normal year at Leicester. See our Fees and Funding section for details.
You will undertake a programme of training and practical experience that is agreed between the sponsoring company and the University. A member of staff will be individually assigned to you as your industrial placement tutor, who will be in regular contact with you throughout your placement and will visit the sponsoring company.
A year in industry is a great opportunity which can give you first-hand experience of working in a mathematics-related career while also enhancing your employability skills and allowing you to network with people in industry.
Modules shown represent choices available to current students. The range of modules available and the content of any individual module may change in future years.
Final year
Final year
Modules
Semester 1
Core modules
- Mathematics with AI Project (year long project)
- Machine Learning for Data Analysis and Artificial Intelligence
Optional modules
- Markov Processes
- Mathematical Modelling
- Operational Research
- Scientific Computing
- Financial Engineering
- Computers, Society and Professionalism
- Computational Intelligence and Software Engineering
Semester 2
Core modules
Semester 2
Optional modules
- Generalised Linear Models
- Introduction to Functional Data Analysis
- Nonlinear Optimisation
- Complex Analysis
- Communicating Mathematics
- Analysis and Design of Algorithms
Modules shown represent choices available to current students. The range of modules available and the content of any individual module may change in future years.
Why Leicester
We have a thriving, student-led Maths Society (SUMS) and Leicester Actuarial Science Society (LASS) which organise social activities and guest lectures throughout the year.
Joint 1st for employability in the UK, with 94% of graduates in skilled work or further study 15 months after graduation (The Guardian, 2025).
UK Top 30 (Complete University Guide, 2026) and 3rd in the UK for Mathematics (Daily Mail 2026).
Our academic staff have written and edited dozens of books and publish regularly in major national and international journals. Where other people only get to read what our experts think, you will be working directly with them, learning from them in lectures and questioning them in seminars.
Teaching and learning
Teaching
As well as lectures, your course will involve regular group meetings, run by both staff and other students, where students’ work is discussed. You will gain experience in presenting mathematical arguments to fellow students, which will enhance and develop your presentation and communication skills.
A typical week for a first or second year student might consist of nine or ten hours of lectures, around four hours of small group working and about three hours of problem classes or computer classes. You will also spend several hours a week on private study: review of lecture material, problem solving, additional reading and preparing for tutorials.
Assessment
Assessment will be via course work, computational exercises, projects and written exams.
Independent learning
When not attending lectures, seminars or other timetabled sessions you will be expected to continue learning independently through self-study. Typically, this will involve reading journal articles and books, working on individual and group projects, undertaking research in the library, preparing coursework assignments and presentations, and preparing for exams. To help with your independent learning, you can access the Library and our social study spaces in halls of residence.
Your contact hours will depend on the option modules you select. You can see details of the contact hours on individual module pages.
Academic support
Our Centre for Academic Achievement provides help for:
- study and exam skills
- academic writing
- presentations
- dissertations
- numerical data skills
- referencing sources
Our AccessAbility Centre offers support and practical help for students with dyslexia or other specific learning difficulties, including physical, mental health or mobility difficulties, deafness, or visual impairment.
Teaching staff
You will be taught by an experienced teaching team whose expertise and knowledge are closely matched to the content of the modules on the course. PhD research students who have undertaken teacher training may also contribute to the teaching of seminars under the supervision of the module leader. Our teaching is informed by the research we do. You can learn more about our staff by visiting our staff profiles.
Apply now
| Course | Qualification | Duration | Attendance | UCAS Code | Start Dates | Availability |
|---|---|---|---|---|---|---|
| Course Mathematics with Data Science and Artificial Intelligence | Qualification BSc | Duration 3 years | Attendance Full-time | UCAS Code G120 | Start Dates September 2026 |
Availability
This course is being advertised subject to approval. |
| Course Mathematics with Data Science, Artificial Intelligence with Year in Industry | Qualification BSc | Duration 4 years | Attendance Full-time | UCAS Code G121 | Start Dates September 2026 |
Availability
This course is being advertised subject to approval. |
