BSc Mathematics with Computer Science
Entry requirements
A level: AAA or AABB including Mathematics (grade A) IB: Pass, with 36 points overall with 18 at Higher Level, including 6 points from Higher Level Mathematics (Preferred Mathematics module is Analysis and Approaches, but Applications and Interpretation is also considered)
About this course
Bachelor of Science in Mathematics with Computer Science, a mathematics and computer science degree focusing on computational and analytical techniques. Core topics include Programming, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Project Management, Environmental Analysis, Artificial Intelligence & Machine Learning. The curriculum blends foundational mathematics with information systems and computing technologies. The first year establishes core mathematical and computing principles through compulsory modules such as Calculus I, Linear Algebra I, and Programming I, alongside optional algorithmics. The second year progresses into advanced mathematical theory and applications with compulsory modules like Analysis and Partial Differential Equations, alongside numerous optional areas spanning finance, geometry, and statistics. The final year centres on independent research through the compulsory Mathematics Project module, complemented by a broad range of optional modules covering advanced mathematics, machine learning, and specialised applications.
Modules
- Calculus I
- Calculus II
- Computational Mathematics
- Core Skills for Mathematicians I
- First Year Mathematics Workshop
- Introduction to Statistics
- Linear Algebra I
- Linear Algebra II
- Programming I
- Algorithmics
- Programming II
- Analysis
- Core Skills for Mathematicians II
- Partial Differential Equations
- Algorithms
- Fields and Fluids
- Financial Mathematics
- Fundamentals of Data Science in R
- Geometry and Topology
- Graph Theory
- Group Theory
- Introduction to Operational Research
- Numerical Analysis
- Statistical Inference
- Statistical Modelling I
- Stochastic Processes
- Vector Calculus and Complex Variable Theory
- Mathematics Project
- Actuarial Mathematics I
- Actuarial Mathematics II
- Advanced Fluid Dynamics
- Advanced Partial Differential Equations
- Algebraic Topology
- Complex Analysis
- Complex and Integral Transform Methods
- Computational Statistical Inference
- Design and Analysis of Experiments
- Further Number Theory and Cryptography
- Galois Theory
- Geometry and Data
- Hilbert Spaces
- Infinite Groups
- Learning and Teaching Mathematics
- Machine Learning
- Mathematical Biology
- Mathematical Finance
- Mathematical Programming
- Numerical Partial Differential Equations
- Optimization
- Project Management
- Relativity, Black Holes and Cosmology
- Statistical Methods in Insurance
- Statistical Modelling II
- Structure and Dynamics of Networks
- Survival Models