BSc Mathematics (Placement Year)
Entry requirements
A level: AAA. This should include Mathematics grade A or Further Mathematics grade A. The overall offer grades will be lowered to AAB for applicants who achieve both Mathematics and Further Mathematics at grades AB, in either order. IB: 36 points overall with 16 points from the best 3 HL subjects including 6 in Mathematics HL (either analysis and approaches or applications and interpretations)
About this course
BSc Hons in Mathematics (Placement Year), a mathematics degree centred on quantitative reasoning, analytical methods and problem-solving. Core topics include Programming, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Accounting, Critical & Analytical Thinking, Human Behaviour, and Artificial Intelligence & Machine Learning. The four-year curriculum includes a mandatory third-year professional placement in a graduate-level role, supported by the university careers service. The first year introduces foundational mathematical concepts through compulsory modules including Logic and Discrete Mathematics, Symmetry and Sequences, Matrices and Calculus, and Probability and Statistics. Students also choose additional subjects such as The Physical Universe, Principles of Macroeconomics, and Languages. Year 2 advances analytical capabilities with core modules such as Linear Algebra, Real Analysis, Multivariate Probability and Statistics, and Project Skills, alongside optional topics like Applied Data Science and Mathematics of Artificial Intelligence. Following the third-year placement, Year 4 comprises entirely optional modules allowing deep specialisation in areas such as Commutative Algebra, Knots and Geometry, Mathematical Cryptography, Advanced Differential Equations, Medical Statistics, and Stochastic Processes.
Modules
- Logic and Discrete Mathematics
- Symmetry and Sequences
- Matrices and Calculus
- Probability and Statistics
- Mathematical Modelling and Programming
- Multivariate Calculus
- Computing Essentials: Programming
- Computing for Business Decision Making
- The Physical Universe
- Fields, Matter and Quantum Physics
- Managing Uncertainty in Business
- Principles of Macroeconomics
- Principles of Microeconomics
- Languages
- Foundations of Accounting and Finance
- Linear Algebra
- Real Analysis
- Multivariate Probability and Statistics
- Project Skills
- Abstract Algebra
- Applied Data Science
- Complex Analysis
- Mathematics of Artificial Intelligence
- Real-world Dynamics
- Placement
- Commutative Algebra
- Hilbert Spaces
- Knots and Geometry
- Metric Spaces and Topology
- Representation Theory
- Graph Theory and Algorithms
- Mathematical Cryptography
- Advanced Differential Equations
- Linear Systems
- Mathematics of Generative Modelling
- Environmental Statistics
- Medical Statistics
- Statistical Inference
- Statistical Learning and Prediction
- Mathematical Finance
- Stochastic Processes
- Mathematical Education
- Mathematical Education Placement
- Optimisation for Machine Learning