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University of Leicester

Mathematics and Artificial Intelligence

UCAS Code: G108

Bachelor of Science (with Honours) - BSc (Hons)

Entry requirements


A level

A,A,B-A,B,B

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. We may consider substantial Level 3 Maths Access credits in place of A-level Maths. Please contact [email protected] regarding eligibility.

Considered when combined with other qualifications.

Considered when combined with other qualifications.

International Baccalaureate Diploma Programme

30

Including 5 points in HL Mathematics.

Leaving Certificate - Higher Level (Ireland) (first awarded in 2017)

H2,H2,H2,H2,H3

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)

D*DD

plus A-Level Mathematics at grade A-B.

Scottish Advanced Higher

A,B,B

Including Mathematics.

Scottish Higher

A,A,B,B,B

Including A in Maths.

Accepted in combination with other qualifications, including Mathematics A-Level.

UCAS Tariff

128-152

We've calculated how many Ucas points you'll need for this course.

About this course


Course option

3.0years

Full-time | 2021

Subjects

Mathematics

Artificial intelligence

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.

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.

Modules

For further details, see the full programme summary on our website by clicking on the ‘view course details’ link towards the top of this page. From there you can access specific module information on the ‘Study with us’ pages.

The Uni


Course location:

University of Leicester

Department:

Mathematics

TEF rating:
Read full university profile

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.

68%
low
Mathematics

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.

Mathematics

Teaching and learning

57%
Staff make the subject interesting
79%
Staff are good at explaining things
67%
Ideas and concepts are explored in-depth
61%
Opportunities to apply what I've learned

Assessment and feedback

Feedback on work has been timely
Feedback on work has been helpful
Staff are contactable when needed
Good advice available when making study choices

Resources and organisation

83%
Library resources
77%
IT resources
85%
Course specific equipment and facilities
70%
Course is well organised and has run smoothly

Student voice

Staff value students' opinions

Who studies this subject and how do they get on?

88%
UK students
12%
International students
62%
Male students
38%
Female students
85%
2:1 or above
22%
Drop out rate

Most popular A-Levels studied (and grade achieved)

A
C
C

Computer science

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?

79%
UK students
21%
International students
83%
Male students
17%
Female students
82%
2:1 or above
20%
Drop out rate

Most popular A-Levels studied (and grade achieved)

B
C
B

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.

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.

£23,000
med
Average annual salary
94%
med
Employed or in further education
89%
high
Employed in a role where degree was essential or beneficial

Top job areas of graduates

22%
Business, finance and related associate professionals
20%
Business, research and administrative professionals
15%
Information technology and telecommunications professionals

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.

Computer science

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.

£28,000
high
Average annual salary
96%
med
Employed or in further education
85%
med
Employed in a role where degree was essential or beneficial

Top job areas of graduates

73%
Information technology and telecommunications professionals
8%
Information technology technicians
4%
Business, finance and related associate professionals

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.

What about your long term prospects?

Looking further ahead, below is a rough guide for what graduates went on to earn.

Mathematical sciences

The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.

£20k

£20k

£30k

£30k

£33k

£33k

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.

Computer science

The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.

£25k

£25k

£33k

£33k

£38k

£38k

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.

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This is what the university has told Ucas about the criteria they expect applicants to satisfy; some may be compulsory, others may be preferable.

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This is the percentage of applicants to this course who received an offer last year, through Ucas.

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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.

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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.

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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).

We calculate a mean rating of all responses to indicate whether this is high, medium or low compared to the same subject area at other universities.

Have a question about this info? Learn more here

This information is from the Higher Education Statistics Agency (HESA).

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