Mathematics and Artificial Intelligence
Entry requirements
A level
including Mathematics.
2 AS Levels accepted in place of 1 A-Level. Accepted in combination with other qualifications, including Mathematics A-Level grade A-B.
Access courses considered require a minimum of 45 credits at level 3, 30 of which must be at Distinction. Plus Mathematics A-Level grade A-B.
Considered when combined with other qualifications.
Considered when combined with other qualifications.
International Baccalaureate Diploma Programme
Including 5 points in HL Mathematics.
Leaving Certificate - Higher Level (Ireland) (first awarded in 2017)
including H2 in Mathematics.
Accepted in combination with Mathematics A-Level.
Accepted in combination with other qualifications, including Mathematics A-Level.
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016)
plus A-Level Mathematics at grade A-B.
Scottish Advanced Higher
Including Mathematics.
Scottish Higher
Including A in Maths.
Accepted in combination with other qualifications, including Mathematics A-Level.
UCAS Tariff
We've calculated how many Ucas points you'll need for this course.
About this course
A strong foundation in mathematical knowledge and technical skills is essential for the development of modern Artificial Intelligence systems. This course will equip you to work in this exciting field.
Large and growing streams of data are ubiquitous in modern society and form the backbone of modern healthcare, public safety, services and science. Sustained functioning and progress in these essential areas depend on the ability to extract and process information from large and growing data. Since processing overwhelmingly large volumes of data can no longer be accomplished by humans alone, we must rely on Artificial Intelligence (AI) systems built on state-of-the-art machine learning and data analytics technologies.
AI systems have evolved dramatically in recent years; from being the subject of academic research with only focused and highly specialised practical uses, to the level of commonly accepted and widely-used technology. Industrial giants such as Google, Amazon, IBM and Microsoft have already embraced the new technology and are offering a broad and rapidly expanding range of AI-based services, including intelligent image and sound processing and recognition. Maintaining and developing these services in the years to come will require a significant pool of suitably educated expertise.
The BSc in Mathematics and AI addresses these market needs by offering a prestigious training programme aimed at delivering AI graduates with a solid background in mathematics, modelling, computational and digital skills. The University of Leicester has a strong teaching and research track record in these areas, with academic staff in Mathematics and Informatics producing high-quality research in collaboration with leading industries.
Modules
For more information on this course and a full list of modules, visit the course information page on our website
Assessment methods
For more information on the methods of assessment on this course, visit the course information page on our website
Tuition fees
Select where you currently live to see what you'll pay:
The Uni
University of Leicester
School of Computing and Mathematical Sciences
What students say
We've crunched the numbers to see if overall student satisfaction here is high, medium or low compared to students studying this subject(s) at other universities.
How do students rate their degree experience?
The stats below relate to the general subject area/s at this university, not this specific course. We show this where there isn’t enough data about the course, or where this is the most detailed info available to us.
Artificial intelligence
Sorry, no information to show
This is usually because there were too few respondents in the data we receive to be able to provide results about the subject at this university.
Who studies this subject and how do they get on?
Most popular A-Levels studied (and grade achieved)
Mathematics
Teaching and learning
Assessment and feedback
Resources and organisation
Student voice
Who studies this subject and how do they get on?
Most popular A-Levels studied (and grade achieved)
After graduation
The stats in this section relate to the general subject area/s at this university – not this specific course. We show this where there isn't enough data about the course, or where this is the most detailed info available to us.
Artificial intelligence
What are graduates doing after six months?
This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.
Top job areas of graduates
Artificial intelligence is a very specialist subject taken by less than 100 people a year at the moment, so there is little reliable information available on graduate prospects - bear that in mind when you review the stats above. Graduates taking this type of subject are more likely than other computing graduates to go into further research. However, if you want to find out more specifically about the potential graduate outcomes of a specific course, it's a good idea to go on open days and talk to tutors about what previous graduates have gone on to do.
Mathematics
What are graduates doing after six months?
This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.
Top job areas of graduates
Want to feel needed? This is one of the most flexible degrees of all and with so much of modern work being based on data, there are options everywhere for maths graduates. With all that training in handling figures, it's hardly surprising that a lot of maths graduates go into well-paid jobs in the IT or finance industries, and last year, a maths graduate in London could expect a very respectable average starting salary of £27k. And we're always short of teachers in maths, so that is an excellent option for anyone wanting to help the next generation. And if you want a research job, you'll want a doctorate — and a really good maths doctorate will get you all sorts of interest from academia and finance — and might secure some of the highest salaries going for new leavers from university.
What about your long term prospects?
Looking further ahead, below is a rough guide for what graduates went on to earn.
Artificial intelligence
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£31k
£37k
£39k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
Mathematics
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£22k
£33k
£35k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
Explore these similar courses...
This is what the university has told Ucas about the criteria they expect applicants to satisfy; some may be compulsory, others may be preferable.
Have a question about this info? Learn more here
This is the percentage of applicants to this course who received an offer last year, through Ucas.
Have a question about this info? Learn more here
This is what the university has told Ucas about the course. Use it to get a quick idea about what makes it unique compared to similar courses, elsewhere.
Have a question about this info? Learn more here
Course location and department:
This is what the university has told Ucas about the course. Use it to get a quick idea about what makes it unique compared to similar courses, elsewhere.
Have a question about this info? Learn more here
Teaching Excellence Framework (TEF):
We've received this information from the Department for Education, via Ucas. This is how the university as a whole has been rated for its quality of teaching: gold silver or bronze. Note, not all universities have taken part in the TEF.
Have a question about this info? Learn more here
This information comes from the National Student Survey, an annual student survey of final-year students. You can use this to see how satisfied students studying this subject area at this university, are (not the individual course).
This is the percentage of final-year students at this university who were "definitely" or "mostly" satisfied with their course. We've analysed this figure against other universities so you can see whether this is high, medium or low.
Have a question about this info? Learn more here
This information is from the Higher Education Statistics Agency (HESA), for undergraduate students only.
You can use this to get an idea of who you might share a lecture with and how they progressed in this subject, here. It's also worth comparing typical A-level subjects and grades students achieved with the current course entry requirements; similarities or differences here could indicate how flexible (or not) a university might be.
Have a question about this info? Learn more here
Post-six month graduation stats:
This is from the Destinations of Leavers from Higher Education Survey, based on responses from graduates who studied the same subject area here.
It offers a snapshot of what grads went on to do six months later, what they were earning on average, and whether they felt their degree helped them obtain a 'graduate role'. We calculate a mean rating to indicate if this is high, medium or low compared to other universities.
Have a question about this info? Learn more here
Graduate field commentary:
The Higher Education Careers Services Unit have provided some further context for all graduates in this subject area, including details that numbers alone might not show
Have a question about this info? Learn more here
The Longitudinal Educational Outcomes dataset combines HRMC earnings data with student records from the Higher Education Statistics Agency.
While there are lots of factors at play when it comes to your future earnings, use this as a rough timeline of what graduates in this subject area were earning on average one, three and five years later. Can you see a steady increase in salary, or did grads need some experience under their belt before seeing a nice bump up in their pay packet?
Have a question about this info? Learn more here