MSci Mathematics
Entry requirements
A level: A*AA. This should include Mathematics grade A or Further Mathematics grade A. The overall offer grades will be lowered to AAA for applicants who achieve both Mathematics and Further Mathematics at grades AA. IB: 38 points overall with 17 points from the best 3 HL subjects including 6 in Mathematics HL (either analysis and approaches or applications and interpretations)
About this course
MSci Hons in Mathematics, a Mathematics degree centred on mathematical and computational approaches to quantitative theory. Core topics include Programming, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Research Methods, Accounting, Environmental Analysis, Critical & Analytical Thinking, Human Behaviour, and Artificial Intelligence & Machine Learning. The final year concludes with a substantial individual research project guided by a supervisor. The first year establishes core foundations through Logic and Discrete Mathematics, Symmetry and Sequences, Matrices and Calculus, and Probability and Statistics, alongside optional choices such as Mathematical Modelling and Programming. Year 2 advances analytical capabilities via Linear Algebra, Real Analysis, Multivariate Probability and Statistics, and Project Skills, with further options including Applied Data Science. Year 3 consists entirely of optional modules enabling advanced study in areas such as Commutative Algebra, Medical Statistics, and Mathematical Finance. The fourth year features a compulsory Dissertation alongside advanced Master's level options like Deep Learning, Galois Theory, and Advanced Statistical Modelling.
Modules
- Logic and Discrete Mathematics
- Symmetry and Sequences
- Matrices and Calculus
- Probability and Statistics
- Mathematical Modelling and Programming
- Multivariate Calculus
- Computing Essentials: Programming
- Computing for Business Decision Making
- The Physical Universe
- Fields, Matter and Quantum Physics
- Managing Uncertainty in Business
- Principles of Macroeconomics
- Principles of Microeconomics
- Languages
- Foundations of Accounting and Finance
- Linear Algebra
- Real Analysis
- Multivariate Probability and Statistics
- Project Skills
- Abstract Algebra
- Applied Data Science
- Complex Analysis
- Mathematics of Artificial Intelligence
- Real-world Dynamics
- Commutative Algebra
- Hilbert Spaces
- Knots and Geometry
- Metric Spaces and Topology
- Representation Theory
- Graph Theory and Algorithms
- Mathematical Cryptography
- Advanced Differential Equations
- Linear Systems
- Mathematics of Generative Modelling
- Environmental Statistics
- Medical Statistics
- Statistical Inference
- Statistical Learning and Prediction
- Mathematical Finance
- Stochastic Processes
- Mathematical Education
- Mathematical Education Placement
- Optimisation for Machine Learning
- Dissertation
- Combinatorics
- Galois Theory
- Lie Groups and Lie Algebras
- Measure and Integration
- Operators and Spectral Theory
- Number Theory
- Probability Theory
- Stochastic Calculus for Finance
- Advanced Statistical Modelling
- Clinical Trials
- Computing and Algorithms for Statistics
- Deep Learning
- Epidemiology and Disease Modelling
- Estimation and Inference
- Hidden-Process Models
- Machine Learning
- Survival and Longitudinal Statistics
- Modern Applied Mathematics