University course Β· real outcomes from HESA / Discover Uni Β· part of Careermash
University degree

Computer Science and Mathematics

University College London Β· London
Qualification
Degree
Length
4 yrs
UK fees / yr
Β£9,535
Study
full-time
Robin Β· your guide
Here's the honest picture on this course - what you'd study, whether you'd likely get in, what it pays, and where it leads. Everything's real data.
About this course

Computer science and mathematics together constitute one of the most intellectually powerful combinations available at degree level. Mathematics provides the theoretical foundations on which computing rests, including logic, algebra, analysis, probability, and the theory of computation, while computer science brings those ideas into contact with the design of algorithms, data structures, programming languages, and systems that solve real-world problems. The two disciplines are deeply intertwined, and students who study them together develop an unusually rigorous and generative way of thinking.

At University College London in London, this four-year full-time programme brings you into one of the world's leading computer science and mathematics departments. UCL's research strength in areas including machine learning, algorithms, computational complexity, pure and applied mathematics means that the academic environment is defined by genuine scientific ambition. You will study analysis, algebra, probability, statistics, discrete mathematics, algorithms, data structures, software engineering, artificial intelligence, and machine learning, with the freedom to deepen your knowledge in the mathematical or computational directions that interest you most as the programme progresses.

The rigour expected of you here is substantial, and the rewards in terms of intellectual development and graduate outcomes are correspondingly high.

Graduates from computer science and mathematics programmes are among the most sought-after in the graduate labour market. The combination is valued intensely in technology companies, financial services, data science, artificial intelligence research, cryptography, and consulting. Academic and research careers are natural paths for those who choose to continue, with a strong background for doctoral study in either pure mathematics, computational theory, or applied machine learning.

The degree also provides outstanding preparation for roles in quantitative finance, where mathematical and computational skills combine.

Could you get in?
The grades students arrived with
48-63 pts2%
80-95 pts2%
112-127 pts1%
128-143 pts2%
144-159 pts6%
160-175 pts16%
176-191 pts7%
192-207 pts8%
208-223 pts19%
224-239 pts12%
240+ pts19%
How they qualified
81% got in with A-levels. The rest came in a mix of ways:
A-levels81%
the IB10%
another degree3%
Other3%
other higher education2%
Could I get in? Try your grades
120 UCAS pts
Pay & prospects
90%
In work or further study after
93%
Continue past first year
83%
Student satisfaction
What graduates earn over time
Β£51,000
3 years on
Β£71,000
5 years on
What graduates actually go on to do % of leavers
Information Technology ProfessionalsHighly skilled85%
Managers, directors and senior officialsHighly skilled5%
What students say National Student Survey
83%
of students are satisfied with the course overall
Teaching82%
Assessment & feedback74%
Academic support60%
Well organised76%
Learning resources84%
Student community91%
In students' own words
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A great decision
Coming here has changed how I think. The best part: the course strikes a good balance between theory and practical application. If I'm honest, some seminar groups were too big for meaningful discussion. On the city β€” local cost of living is…
Class of 2024 Β· Full-time
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Genuinely worthwhile
I was sceptical before starting β€” now I'd recommend it to anyone. The best part: small-group tutorials really push your thinking. If I'm honest, a few modules feel under-resourced compared to the flagship ones. On the city β€” the city is a b…
Postgraduate Β· Full-time
More courses like this
Where this degree can lead
Like the look of it?
When you're ready, the full entry requirements and application are on University College London's own site.
Apply on uni site
Careermash Β· real course data from HESA / Discover Uni, in plain English.

Career data: role, pay and progression profiles built for Careermash's careers engine; AI-impact estimates from Anthropic's observed AI-usage telemetry and OpenAI's AI Jobs Transition Framework. Course data: HESA / Discover Uni, including Graduate Outcomes, LEO and the National Student Survey. Apprenticeships: IfATE-published standards, approved only.

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