MMath Mathematics
Entry requirements
A level: AAA/A*AB including A in Maths or AAB including AB in Maths and Further Maths. We recognise the benefit of STEP/MAT/TMUA in demonstrating your aptitude to study Mathematics at a higher level but do not include it as part of any conditions of offer. IB: 37 (6,6,6 HL) including HL Maths BTEC: BTEC Level 3 National Extended Diploma: D*DD plus A level Maths at Grade A. BTEC Level 3 National Diploma: D*D plus A level Maths at Grade A. BTEC Level 3 National Extended Certificate: D* plus two A levels at Grades AA including Maths.
About this course
MMath (Hons) in Mathematics, a mathematics degree centred on analytical and problem-solving approaches to quantitative theory. Core topics include Programming, Statistics, Mathematical Modelling, and Artificial Intelligence & Machine Learning. The curriculum is delivered through a structured progression from foundational theory to advanced research. The first year covers core foundations through Analysis I, Calculus I, Computing and Numerical Methods, Linear Algebra and Geometry I, Mathematical Thinking, Introductory Probability and Statistics, Linear Algebra and Geometry II, and Mechanics. The second year builds on this with Algebra, Analysis II, Calculus II, Probability Theory, Introduction to Differential Geometry, Communicating Mathematics, Complex Analysis, ODEs and Calculus of Variations, and Elements of Topology, alongside optional modules such as Graph Theory, An Introduction to Mathematics Education, Applied Statistics, Analytical Dynamics, Computational Methods for Differential Equations, and Statistical Modelling. In the third year, students undertake a Mathematics Report and select from numerous optional modules like Advanced Numerical Methods, Statistical Machine Learning, Introduction to Algebraic Geometry, Number Theory, Dynamical Systems, Asymptotic Methods, Operational Research, Stochastic Methods in Finance, Functional Analysis, Bayesian Statistics and Markov Chain Monte Carlo Methods, Galois Theory, Medical Statistics, Studies in Science and Mathematics Education, Advanced Complex Analysis, Representation Theory, Linear Differential Equations, Vibrations and Waves, Elliptic Curves, Game Theory, Computational Methods in Finance, Mathematical Biology, and a University-wide Language Programme. The final year centres on the MMath Mathematics Project and advanced options including Statistical Machine Learning, Lie Groups and Lie Algebras, Geometric Structures on Manifolds, Functional Analysis, Advanced Numerical Methods, Measure Theory, Asymptotic Methods, Mathematical Modelling I, Stochastic Models in Finance, Fluid Mechanics, Algebraic Topology, Nonlinear Waves, Theory of PDEs, Static and Dynamic Optimisation, Computational Methods in Finance, Stochastic Calculus and Theory of Pricing, and Mathematical Modelling II.
Modules
- Analysis I
- Calculus I
- Computing and Numerical Methods
- Linear Algebra and Geometry I
- Mathematical Thinking
- Introductory Probability and Statistics
- Linear Algebra and Geometry II
- Mechanics
- Algebra
- Analysis II
- Calculus II
- Probability Theory
- Introduction to Differential Geometry
- Communicating Mathematics
- Complex Analysis
- ODEs and Calculus of Variations
- Elements of Topology
- Graph Theory
- An Introduction to Mathematics Education
- Applied Statistics
- Analytical Dynamics
- Computational Methods for Differential Equations
- Statistical Modelling
- Mathematics Report
- Advanced Numerical Methods
- Statistical Machine Learning
- Introduction to Algebraic Geometry
- Number Theory
- Dynamical Systems
- Asymptotic Methods
- Operational Research
- Stochastic Methods in Finance
- Functional Analysis
- Bayesian Statistics and Markov Chain Monte Carlo Methods
- Galois Theory
- Medical Statistics
- Studies in Science and Mathematics Education
- Advanced Complex Analysis
- Representation Theory
- Linear Differential Equations
- Vibrations and Waves
- Elliptic Curves
- Game Theory
- Computational Methods in Finance
- Mathematical Biology
- University-wide Language Programme
- MMath Mathematics Project
- Statistical Machine Learning
- Lie Groups and Lie Algebras
- Geometric Structures on Manifolds
- Functional Analysis
- Advanced Numerical Methods
- Measure Theory
- Asymptotic Methods
- Mathematical Modelling I
- Stochastic Models in Finance
- Fluid Mechanics
- Algebraic Topology
- Nonlinear Waves
- Theory of PDEs
- Static and Dynamic Optimisation
- Computational Methods in Finance
- Stochastic Calculus and Theory of Pricing
- Mathematical Modelling II