BSc Mathematical Sciences
Entry requirements
A Level: AAB to include Mathematics or Further Mathematics.. IB: 6,6,5 at Higher Level, including Mathematics, with a minimum of 32 points overall.. BTEC: only considered when combined with other qualifications.
About this course
Bachelor of Science in Mathematical Sciences BSc, a mathematics degree exploring analytical concepts and quantitative techniques. Core topics include Programming, Statistics, Mathematical Modelling, and Artificial Intelligence & Machine Learning. The programme focuses on applications directed toward careers in business, industry, or academia. The first year covers the foundations through Differential Equations and Mechanics, Mathematical Discovery: Problem Solving and Programming, Mathematical Foundations, Calculus and Linear Algebra, and Probability, Data and Statistics. The second year introduces Applied Linear Algebra and Optimisation, Graphs and Algorithms, Groups, Rings and Fields, and Metric Spaces and Geometry. In the final year, students undertake a Mathematical Project alongside optional modules such as Deep Learning and Neural Networks, Game Theory, and Number Theory and Cryptography.
Modules
- Differential Equations and Mechanics
- Mathematical Discovery: Problem Solving and Programming
- Mathematical Foundations, Calculus and Linear Algebra
- Mathematical Methods and Applications
- Probability, Data and Statistics
- Mathematical Challenge: Problem Solving and Programming in Business and Industry
- Applied Linear Algebra and Optimisation
- Graphs and Algorithms
- Groups, Rings and Fields
- Mathematical Modelling with Differential Equations
- Metric Spaces and Geometry
- Multivariable and Vector Calculus
- Real and Complex Analysis
- Statistics
- Mathematical Project
- Continuum Mechanics
- Deep Learning and Neural Networks
- Galois Theory and Coding Theory
- Game Theory
- Graph Theory and Applications
- Mathematics in Biology and Medicine
- Mathematics of Financial Derivatives
- Medical Statistics
- Metric Spaces and Geometry
- Number Theory and Cryptography
- Numerical Analysis
- Optimisation
- Partial Differential Equations and Applications
- Real and Complex Analysis
- Statistical Machine Learning
- Statistical Modelling