MMath Mathematics
Entry requirements
A level: AAB including Maths
About this course
MMath in Mathematics. Core topics include Programming, Data Analysis, Statistics, Mathematical Modelling, and Artificial Intelligence & Machine Learning. The third and fourth years offer a wide choice of option modules, allowing specialisation in areas such as actuarial science and statistical inference. The MMath includes a final-year research project not available on the BSc route.
Modules
- Scientific Computing
- Operational Research
- Groups and Symmetry
- Differential Geometry
- Financial Engineering
- Mathematical Modelling
- Equations of Mathematical Physics
- Topology
- Topics in Mathematical Biology
- Nonlinear Optimisation
- Markov Processes
- Generalised Linear Models
- Number Theory
- Communicating Mathematics
- Complex Analysis
- Data Mining and Neural Networks
- Squaring the Circle and Irreducible Polynomials
- Introduction to Functional Data Analysis
- Calculus and Analysis 1
- Linear Algebra 1
- Fundamentals of University Mathematics
- Calculus and Analysis 2
- Linear Algebra 2
- Probability and Statistics
- Elements of Number Theory
- Business Microeconomics
- Programming Fundamentals
- Sets, Relations and Groups
- Business Macroeconomics
- Algorithms, Data Structures and Advanced Programming
- Vector Calculus
- Advanced Linear Algebra
- Introduction to Computing
- Differential Equations
- Algebra
- Investigations in Mathematics
- Actuarial Modelling 1
- Statistical Distributions and Inference
- Advanced Discrete Mathematics
- Mathematical Foundations of AI and Machine Learning
- Statistical Data Analysis
- Industrial Applications of Mathematics
- Actuarial Modelling 2
- Scientific Computing
- Financial Engineering
- Operational Research
- Differential Geometry
- Groups and Symmetry
- Mathematical Modelling
- Topology
- Equations of Mathematical Physics
- Business Microeconomics
- Topics in Mathematical Biology
- Machine Learning for Data Analysis and Artificial Intelligence
- Markov Processes
- Generalised Linear Models
- Number Theory
- Communicating Mathematics
- Data Mining and Neural Networks
- Fields and Classical Geometry
- Complex Analysis
- Introduction to Functional Data Analysis
- Business Macroeconomics
- Nonlinear Optimisation