Mathematics and Computer Science
Entry requirements
A level: A*A*A with the A*s in Maths and Further Maths if available IB: 39 (including core points) with 766 at HL (the 7 must be in Higher Level Mathematics)
About this course
BA or MMathCompSci in Mathematics and Computer Science, a mathematics and computer science degree bridging theoretical foundations with practical applications. Core topics include Programming, Computer Architecture, Mathematical Modelling, and Artificial Intelligence & Machine Learning. The programme is delivered jointly by the Department of Computer Science and the Mathematical Institute. The first year covers core foundations through Analysis, Linear algebra, Probability, Functional programming, and Imperative programming. The second year introduces algorithms and computing concepts via Algorithms and data structures, Models of computation, Artificial Intelligence, and Computer architecture. The third year advances into specialised mathematical theory and computer science topics including Graph theory, Information theory, Computer-aided formal verification, and Machine learning. The fourth year concludes with advanced study options such as Algebraic geometry, Computational biology, Geometric deep learning, and Probabilistic model checking.
Modules
- Analysis
- Groups and group actions
- Introduction to complex numbers
- Introduction to university maths
- Linear algebra
- Probability
- Continuous maths
- Design and analysis of algorithms
- Functional programming
- Introduction to proof systems
- Imperative programming
- Algorithms and data structures
- Group design practical
- Models of computation
- Complex analysis
- Metric spaces
- Numerical analysis
- Quantum theory
- Topology
- Artificial Intelligence
- Computer architecture
- Computer graphics
- Databases
- Logic and proof
- Quantum information
- Commutative algebra
- Galois theory
- Graph theory
- Information theory
- Set theory
- Topology and groups
- Computer-aided formal verification
- Geometric modelling
- Lambda calculus and types
- Machine learning
- Algebraic geometry
- Analytic number theory
- Category theory
- Elliptic curves
- Lie groups
- Model theory
- Probabilistic combinatorics
- Automata, logic and games
- Categories, proofs and processes
- Computational biology
- Database systems implementation
- Foundation of self-programming agents
- Geometric deep learning
- Probabilistic model checking