Teaching and assessment for Mathematics BSc (Hons)

Build confidence in the mathematical foundations needed for university study. Strengthen your skills in algebra, functions, trigonometry, vectors, differentiation, and integration while developing the problem-solving ability that supports future study and quantitative careers. 

Develop the mathematical tools used to describe space, motion, and change. Study integration, differential equations, vectors, matrices, and geometry while building the problem-solving skills needed for advanced study in mathematics and physics.

Learn how mathematicians prove that results are true. Study logic, proof methods, truth tables, induction, contradiction, and number theory while developing the clear reasoning and precision needed for university-level mathematics. 

Learn how statistics and probability are used to understand data, from science to finance. Analyse patterns, model uncertainty, and make informed decisions using real-world information. 

Explore the mathematics of patterns, choices, strategy, and symmetry. Study set theory, combinatorics, game theory, and group theory while building problem-solving skills used in pure mathematics, data science, and decision-making. 

Develop analytical approaches to problem-solving and communication skills that employers value. Work on problem-solving challenges, explore scientific careers, and learn how to present with impact

Starting university is a big step and we’re here to help you make the most of it.

No matter what subject you’re studying, there are important life and study skills that will help you succeed now and in the future.

Explore how mathematics reveals patterns in connected systems.

Study graph theory, shortest paths, graph colouring, maximum flow, and network algorithms.

Use Python to model and visualise road, social, computer, biological, and pipeline networks.

Explore powerful ideas at the heart of advanced mathematics. Study vector calculus, Fourier series, and partial differential equations, and see how they connect pure mathematics with physics, engineering, and mathematical modelling. 

Turn data into evidence using statistics and R.

Learn to visualise data, test ideas, and measure uncertainty while building models that support evidence-based decision-making in research, policy, and industry.

Learn how to solve real-world planning and transport problems using maths. Build practical skills in optimisation, modelling, and decision-making.

Discover the mathematics behind 3D graphics, machine learning, and high-dimensional data.

Study vector spaces, matrices, transformations, eigenvalues, diagonalisation, and orthogonality while developing a deeper understanding of the structure and beauty of linear algebra.

Master programming in Python and MATLAB through hands-on labs. Gain real skills used by scientists and engineers in industry every day. 

Now that you’ve settled into university life, it’s time to build on the foundations you set in your first year.

This second-year module is all about helping you take your development to the next level. This module will cover this from a personal, academic, and professional perspective.

Learn how mathematics is used to solve real-world industry problems.

Translate open-ended challenges into mathematical models, test predictions, understand limitations, and communicate results clearly through a group project and professional report.

Explore the rigorous ideas behind limits, continuity, and convergence.

Study metric spaces, compactness, completeness, and proof, developing the precise logical thinking at the heart of real analysis and pure mathematics.

Model real-world systems using numerical methods. Learn to solve equations, simulate dynamics, and code like a computational scientist.

In finance and energy you often want to maximise profit. There are however constraints from the operational side of the business that must be adhered to. This gives rise to what are known in mathematics as constrained optimisation problems. In this module, you'll study optimisation methods to solve these problems.

Study how systems evolve over time. Learn how to model and analyse physical and biological systems using differential equations and qualitative methods.

Explore calculus in the complex plane.

Study complex functions, contour integrals, residues, and conformal mapping.

See how complex analysis connects geometry, algebra, pure mathematics, and applications such as electrostatics.

Apply mathematics beyond the lecture theatre through an approved summer placement or internship.

Reflect on your experience, gain academic credit, enhance your CV, and show future employers how your mathematical skills can be used to solve practical problems.

Discover how mathematics can explain living systems.

Use differential equations to model epidemics, nerve signals, travelling waves, and biological pattern formation, from animal coat markings to how shapes form during development.

Discover the mathematics behind reliable data analysis.

Study probability distributions, estimation, hypothesis testing, regression, and generalised linear models.

Use R to connect mathematical statistics with real data analysis and evidence-based decision-making.

Learn how differential equations can be solved when exact formulae are not available.

Study numerical approximation methods for ODEs and PDEs, and analyse how error, stability, and convergence determine whether an approximation can be trusted.

Learn how to build and test machine learning models in Python using tools like TensorFlow. Develop the practical coding skills industry needs.