BSc Mathematics
Entry requirements
A level: AAB (B in Maths)
About this course
BSc in Mathematics, combining statistical methods with computational techniques. Core topics include Data Analysis, Statistics, Mathematical Modelling, and Artificial Intelligence & Machine Learning. The course covers core areas including calculus, algebra, and statistics, with options to explore operational research and mathematical modelling. The course begins with foundational modules before progressing to specialized topics such as algebraic topology and fluid dynamics.
Modules
- Computing for Mathematics
- Foundations of Mathematics I
- Foundations of Mathematics II
- Linear and Differential Equations
- Probability and Statistics
- Mathematical Creativity and Geometry
- Linear Algebra and Multivariable Calculus
- Real Analysis
- Probability Theory and Stochastic Simulation
- Modern Mathematical Computing
- Abstract Algebra
- Mechanics
- Operational Research
- Introduction to Functional and Fourier Analysis
- Algebraic Topology
- Differential Geometry of Curves and Surfaces
- Introduction to Number Theory 2
- Algebra II: Rings
- Algebra III: Fields
- Measure Theory
- Complex Analysis and Functional Series
- Knot Theory
- Theori Clymau
- Methods of Applied Mathematics
- Fluid Dynamics
- Solid Mechanics
- Project Module (Full Year)
- Project Module (Half)
- Project Module (Half) Spring Semester
- Stochastic Processes for Finance and Insurance
- Statistical Modelling
- Time Series
- Big Data Technologies
- Algorithms and Heuristics
- Optimisation
- Game Theory
- Algorithmau a Dulliau Hewristig / Algorithms and Heuristics
- Mathematics of AI and Deep Learning
- Developing Mathematics Teachers for Future Generations
- Prosiect
- Modiwl Prosiect (Hanner) Semester yr Hydref
- Modiwl Prosiect (Hanner) Semester y Gwanwyn