COURSE CURRICULUM

The Mathematics degree offers a comprehensive foundation in pure, applied, and statistical mathematics, alongside practical computational skills. In Year 1, students are introduced to fundamental mathematical tools through core modules such as Vectors and Matrices, Calculus and Mathematical Analysis, and Discrete Mathematics. Modules like Mathematical Coding and Analysis of Data develop essential programming and data analysis skills using modern software. Other modules such as Probability and Randomness and Our Mathematical World broaden understanding of statistical thinking and the historical and cultural context of mathematics.In Year 2, the curriculum builds upon the first-year foundations with modules like Linear Algebra and Differential Equations and Vector Calculus, which deepen understanding of mathematical methods and their applications. Students explore practical and industry-relevant topics through Numerical Mathematics, Operational Research, and Simulation and Modelling. Statistical Data Analysis and Time Series further develop students’ data handling abilities and introduce concepts from time series and machine learning.In Year 3, students complete advanced modules in Optimisation Techniques and Linear Models and Statistical Inference, focusing on decision-making, modelling, and data interpretation. A wide range of optional modules allows students to tailor their studies toward specific interests or career paths. These include Machine Learning, Actuarial Mathematics and Risk Modelling, Financial Time Series, Bayesian Methods, Graph Theory, Mathematics for the Life Sciences, Coding and Cryptography, and Partial Differential Equations. Students also undertake a major final-year project, choosing from a Research Project, a Mathematics Work Placement, or participation in the Undergraduate Ambassadors Scheme for mathematics education.Overall, the degree equips students with strong analytical, quantitative, and problem-solving skills. It places emphasis on practical experience and real-world applications, particularly in data science, finance, computing, and education. Graduates are well-prepared for a wide range of careers in industry, government, teaching, and postgraduate study.