BSc Mathematics with a Year in Industry
Entry requirements
A Level: AAA to include A-level grade A in Mathematics or Further Mathematics.. IB: 6,6,6 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 Mathematics with a Year in Industry, a mathematics degree focusing on analytical methods and industry placement. Core topics include Programming, Data Analysis, Statistics, Mathematical Modelling, and Artificial Intelligence & Machine Learning. Students complete a dedicated professional placement in their third year. The first year introduces foundational principles through modules such as Differential Equations and Mechanics, Mathematical Foundations, Calculus and Linear Algebra, and Probability, Data and Statistics. The second year advances core knowledge with Applied Linear Algebra and Optimisation, Graphs and Algorithms, Groups, Rings and Fields, and Metric Spaces and Geometry. The final year involves independent research via the Mathematical Project alongside advanced study in areas such as Data Science and Machine Learning, Number Theory and Cryptography, and Statistical Modelling.
Modules
- Differential Equations and Mechanics
- Mathematical Discovery: Problem Solving and Programming
- Mathematical Foundations, Calculus and Linear Algebra
- Probability, Data and Statistics
- Real Analysis
- 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
- Year in Industry (Mathematics)
- Mathematical Project
- Combinatorics and Computation
- Continuum Mechanics
- Data Science and Machine Learning
- Galois Theory and Coding Theory
- Game Theory
- Geometry and Mathematical Physics
- Graph Theory and Applications
- Mathematics in Biology and Medicine
- Mathematics of Financial Derivatives
- Measure Theory and Functional Analysis
- Medical Statistics
- Number Theory and Cryptography
- Numerical Analysis
- Optimisation
- Partial Differential Equations and Applications
- Statistical Machine Learning
- Statistical Modelling
- Topology