Oxford requirement to study Computer Science; www.ox.ac.uk

UCAS code G400 Duration 3 years (BA)
4 years (MCompSci)
Admissions requirements A*AA, with the A* in Maths, Further Maths or Computing/Computer Science Subject requirements   Maths
  Further Maths
Admissions test(s) ox.ac.uk/mat Written work None
Admissions statistics* Interviewed: 19%
Successful: 6%
Intake: 41
*3-year average 2019-21
Contact +44 (0) 1865 273821 / 283507
Email Computer Science

Subject requirements:       Essential       Recommended       Helpful – may be useful on course

Unistats information for this course can be found at the bottom of the page

Please note that there may be no data available if the number of course participants is very small.

Computer science is about understanding computer systems and networks at a deep level. Computers and the programs they run are among the most complex products ever created; designing and using them effectively presents immense challenges. Facing these challenges is the aim of computer science as a practical discipline, and this leads to some fundamental questions:

  • How can we capture in a precise way what we want a computer system to do?
  • Can we mathematically prove that a computer system does what we want it to?
  • How can computers help us to model and investigate complex systems like the Earth’s climate, financial systems or our own bodies?
  • What are the limits to computing? Will quantum computers extend those limits?

The theories that are now emerging to answer these kinds of questions can be immediately applied to design new computers, programs, networks and systems that are transforming science, business, culture and all other aspects of life.

Computer Science can be studied for three years (BA) or four years (Master of Computer Science). The fourth year allows the study of advanced topics and an in-depth research project. Students do not need to choose between the three-year and four-year options when applying to the course; all students apply for the four-year course, and then decide at the start of the third year whether they wish to continue to the fourth year (which is subject to achieving a 2:1 at the end of the third year).

The course concentrates on creating links between theory and practice. It covers a wide variety of software and hardware technologies and their applications. We are looking for students with strong mathematical ability, which you will develop into skills that can be used both for reasoning rigorously about the behaviour of programs and computer systems, and for applications such as scientific computing. You will also gain practical problem-solving and program design skills; the majority of subjects within the course are linked with practical work in our well-equipped laboratory.

A typical week

During the first part of the course, your work will be divided between about ten lectures and two tutorials each week, in addition to about two practical sessions. In tutorials you will discuss ideas in depth with an experienced computer scientist, usually with just one or two other students. You will be expected to spend a considerable amount of time developing your own understanding of the topics covered in lectures, answering questions designed to check your understanding, and preparing for tutorials.

As the course progresses, you will also begin to work in small classes of up to ten people on more specialised topics. In the second year you will take part in a group design practical, which may be sponsored by industry. In Years 3 and 4 about a third of your time is spent working on your chosen individual project. Most tutorials, classes, and lectures are delivered by staff who are tutors in their subject. Many are world-leading experts with years of experience in teaching and research. Some teaching may also be delivered by postdoctoral researchers or postgraduate students who are studying at doctorate level.

To find out more about how our teaching year is structured, visit our Academic Year page.

Course structure


  • Core courses (100%):
    • Continuous mathematics
    • Design and analysis of algorithms
    • Digital systems
    • Discrete mathematics
    • Ethics and responsible innovation
    • Functional programming
    • Imperative programming
    • Introduction to formal proof
    • Linear algebra
    • Probability

Four exam papers


  • Core courses (50%):
    • Algorithms
    • Compilers
    • Concurrent programming
    • Models of computation
    • Group design practical
  • Current options (50%) include:
    • Computer architecture
    • Computer graphics
    • Computer networks
    • Databases
    • Artificial intelligence
    • Logic and proof

Eight exam papers


  • Current options (67%) include:
    • Computational complexity
    • Machine learning
    • Computer security
    • Computer-aided formal verification
    • Geometric modelling
    • Knowledge representation and reasoning
    • Lambda calculus and types
    • Principles of programming languages
  • Optional project work (33%)*

Six exam papers plus project report, or eight exam papers


  • Current options (62%) include:
    • Advanced topics in machine learning
    • Automata, logic and games
    • Advanced security
    • Categories, proofs and processes
    • Computational game theory
    • Computational learning theory
    • Concurrent algorithms and data structures
    • Database systems implementation
    • Probabilistic model checking
    • Probability and computing
    • Quantum software
    • Requirements
  • Project work (38%)

The courses listed above are illustrative and may change. A full list of current options is available on the Computer Science website.


Five take-home exams or written papers plus project report

The content and format of this course may change in some circumstances. Read further information about potential course changes.

* To be confirmed


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