Enter OTP
Computer science is about understanding computer systems and networks at a deep level. You will use your understanding of mathematical reasoning to reason rigorously about the behaviours of computer programmes and systems.This course concentrates on creating links between theory and practice, covering a wide variety of software and hardware technologies and their applications.The course offers the opportunity to develop more understanding of Computer Science as a subject, and focuses on the mathematical underpinnings of computer science. It offers the opportunity to gain practical problem-solving and programme design skills.
Curriculum Structure
Year 1
You’ll build a strong foundation through core modules such as Functional Programming, Imperative Programming, Design and Analysis of Algorithms, Discrete Mathematics, Continuous Mathematics, Digital Systems, Linear Algebra and Probability. These are taught via lectures, tutorials, and practical lab sessions—ensuring you can both reason rigorously and code effectively.
Year 2
Your second year deepens core knowledge with courses like Algorithms and Data Structures, Compilers, Concurrent Programming, and Models of Computation. Alongside four optional papers—including choices like Computer Architecture, Databases or Artificial Intelligence. You’ll as well collaborate in a group design practical, often in industry partnership.
Year 3
With two-thirds of the year spent on computer science options, you’ll choose from modules such as Computational Complexity, Machine Learning, Computer Security, or Formal Verification, and complete an individual project that drives deeper specialist knowledge .
Year 4 (optional MCompSci)
For those pursuing the four-year Master's route, Year 4 brings advanced courses like Advanced Security, Quantum Software, Deep Learning in Healthcare along with a substantial research-focused project. Most exams this year are take-home, and the project report is a cornerstone of the degree.
Focus areas: Foundations of algorithms and programming • System architecture • Theoretical and applied computing • Specialized topics such as AI, security, quantum computing
Assessment
Assessment combines written examinations, programming assignments, and project work, alongside intensive tutorial feedback from your college tutors
Year 1 includes four exam papers.
Year 2 includes eight exam papers and group Design Practical assessed by a demonstration and presentation.
Year 3 includes six exam papers plus project report, or eight exam papers.
Year 4 includes five take-home exams or written papers plus project report.
The Oxford tutorial
College tutorials are central to teaching at Oxford. Typically, they take place in your college and are led by your academic tutor(s) who teach as well as do their own research. Students will also receive teaching in a variety of other ways, depending on the course. This will include lectures and classes, and may include laboratory work and fieldwork. However, tutorials offer a level of personalised attention from academic experts unavailable at most universities.
During tutorials (normally lasting an hour), college subject tutors will give you and one or two tutorial partners feedback on prepared work and cover a topic in depth. The other student(s) in your tutorials will typically be doing the same course as you and covering the same topic. Such regular and rigorous academic discussion develops and facilitates learning in a way that isn’t possible through lectures alone. Tutorials also allow for close progress monitoring so tutors can quickly provide additional support if necessary.
Professional alignment (accreditation): The programme is fully aligned with UK and international standards in computing education; Oxford’s degree is widely recognised and meets academic requirements for chartered status in engineering and computing.
Reputation (employability rankings):
Ranked #1 worldwide for Computer Science by Times Higher Education in 2025 (subject score: 98.3, research 99.4, teaching 99.2)
QS ranks Oxford Computer Science among the Top 5 globally in 2025.
Graduate outcomes are exceptional: 95% employed or in further study within six months, with average starting salaries around £65,000
At Oxford you’ll learn in the Wolfson Building (Parks Road) and across the Alan Turing Building, which includes dedicated low‑vibration laboratories, software labs (Windows, Linux, high‑spec design suites), and lecture theatres—all equipped with professional-grade tools like MATLAB, SolidWorks and access to your own computer for remote lab work. The University offers gigabit networking, eduroam Wi‑Fi, and comprehensive support like Canvas modules, podcasted lectures, and free software (Office 365, virus protection).
Experiental Learning Highlights
Structured practicals & software labs: Regular lab sessions (OCaml, Java, Python, systems) using Windows and Linux workstations in Software Labs A/B in the Turing Building .
Group design practical (Part II): In second year you'll collaborate in teams on industry-sponsored projects (Microsoft, IBM), guided in real labs.
Individual project (Part III/IV): Supervised in-depth projects in your final years, making up ~25% of your exam marks, using departmental clusters and Unix/Linux workstations.
Tutorials & tutorials-linked seminars: Weekly tutorials (two–three students with a tutor) plus small classes and others seminars—a key hands-on learning method.
Seminars & industry talks: Attend research seminars (Cybersecurity, AI, Verification) and lunchtime Industry Seminars featuring Amazon, Google, Bloomberg, Credit Suisse and others.
Summer internships & work experience: Although not compulsory, many students secure summer industry placements via the Careers Service and departmental support. Examples include Google SRE, Amazon testing, Fatsoma, Semmle, and Deutsche Bank.
High-performance clusters & networks: Use departmental HPC clusters, parallel computing systems, superfast University-wide network, and remote desktop facilities—everything connects via eduroam.
Top-tier research institutes: Collaboration opportunities with Oxford’s Robotics Institute, e‑Research Centre, and Centre for Quantum Computation.
Cutting-edge lab space: The Turing Building contains three software labs: Windows, Linux, and high-spec 3D design; plus low‑vibration labs for precise research.
Oxford doesn’t just teach you concepts it plunges you into real computing environments: collaborative coding, labs, seminars, independent projects, summer placements, and strong ties to world-class research centres. This is precisely the kind of preparation that employers, and PhD programs, value.
Oxford Computer Science graduates enjoy outstanding career prospects: with 95–100% in employment or further study within six months and average starting salaries between £45 k–£52 k (rising to around £65 k after five years). Key roles they pursue include:
Senior Software Engineer or Developer
Data Scientist or AI Specialist
Quantitative Analyst or FinTech Consultant
Technical Lead or Product Architect
University services that support employment
The Oxford Careers Service offers personalized counseling, workshops, interview prep, and access to over 200 career fairs and employer events annually. The CS department additionally facilitates world-class internship opportunities with firms like Google, Amazon, IBM, Cisco, Morgan Stanley, Goldman Sachs and others.
University–industry partnerships
The CS Department maintains strong ties with industry via collaborative R&D initiatives, internships, sponsorships, project support, and masters’ project supervision from corporate partners.
Long-term accreditation & reputation
The CS department is consistently ranked #1 in the world by The Times Higher Education (2019–2021) and #5 globally per QS Rankings 2020 This top-tier accreditation carries lifelong prestige.
Graduation outcomes
• 95% of leavers gain high-skilled employment or continue to further study
• Alumni enter cutting-edge roles in computing, finance, academia, government policy, consultancy, and entrepreneurship
Further Academic Progression:
After earning your degree, you can seamlessly pursue further study. Many students go on to:
Oxford MSc and DPhil (PhD) programs in areas like AI, Machine Learning, Quantum Computing
Postgraduate research (DPhil) in robotics, cybersecurity, data science or theoretical CS
Specialized professional masters (e.g. MSc in Computer Science)
JD (Law), MBA or interdisciplinary postgraduate routes, leveraging strong methodological foundations from the CS program
International Baccalaureate (IB): 39 (including core points) with 766 at HL (the 7 must be in HL Mathematics)CBSE board: Grades A1 A1 A1 A2 A2, with grade A1 in any subjects relevant to CSAdmission Test: MAT with test dates on 22 and 23 October 2025. Registration Deadline: TBDCandidates are expected to have Mathematics to A-level (A* or A grade), Advanced Higher (A grade), Higher Level in the IB (score 7) or another equivalentUCAS Application • Official High School Transcripts • Personal Statement • Educational Resume • Letter of Recommendation by School TeacherApplicants are selected for interview by their proven mathematical talent, the ability to think and work independently, the capacity to absorb and use new ideas, and enthusiasm alongside the Mathematics Admissions Test (MAT) results.For CISCE board: Overall grade of 90% or more, with grades of at least 95% or above in three subjects (including any relevant to the course applied for) and 85% or above in the other two subjects. Software DeveloperData AnalystBusiness Intelligence AnalystWeb DeveloperIT Support SpecialistSystems AnalystDatabase AdministratorCybersecurity AnalystCloud EngineerUX/UI Designer
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University of Oxford
