Swansea University

What you'll study

The programme introduces core mathematical concepts in the first year and progressively moves to more specialised topics in later years. Core topics include calculus and analysis, linear algebra, discrete mathematics, ordinary differential equations, and introductory probability and statistics. Mathematical computation and programming are embedded throughout, with training in numerical methods and the use of mathematical software.

• Foundations: limits, continuity, differentiation and integration; matrix algebra; introductory proofs and mathematical reasoning.
• Core topics: real analysis, abstract algebra (groups, rings, fields), multivariable calculus, complex variables, and ordinary differential equations.
• Applied and computational mathematics: numerical analysis, scientific computing, mathematical modelling of physical and biological systems, and algorithmic methods.
• Probability and statistics: probability theory, statistical inference, stochastic processes and an introduction to data analysis techniques.
• Options and advanced modules: topology, partial differential equations, optimisation, financial mathematics, cryptography, time series, machine learning methods and project work or dissertation in a topic of choice.

Students typically progress from structured lectures and lab-based computing sessions to small-group tutorials and supervised project work. A final-year research project allows you to specialise in an area of interest and develop independent problem-solving and communication skills.

Entry requirements

Successful applicants will normally have strong mathematics qualifications. Typical applicants hold A-level Mathematics; Further Mathematics is highly recommended and strengthens an application. Mathematics-based qualifications such as IB Mathematics, BTEC with strong mathematics-related units, or equivalent international credentials are also considered.

• Academic profile: A strong pass in a recognised school-leaving qualification with a substantial mathematics component.
• Preferred subjects: A-level Mathematics is normally required; Further Mathematics is advantageous. Candidates from quantitative subjects (physics, engineering, computer science) are welcomed.
• Other applicants: Mature students, graduates in other disciplines, and international applicants are considered on their prior qualifications and suitability for the course.

Career prospects

Graduates with a BSc in Mathematics have highly transferable skills prized by employers: analytical reasoning, numerical competence, modelling, and programming. Career routes taken by alumni include:

• Data science, analytics and machine learning roles in technology and business.
• Actuarial careers and risk analysis in insurance and pensions (further actuarial exams usually required).
• Quantitative roles in finance, banking and investment management.
• Software development, algorithm design and IT consultancy.
• Engineering and scientific modelling posts in industry and government.
• Teaching mathematics at secondary level (with appropriate teacher training) and academic research through postgraduate study (MSc, PhD).

The degree’s emphasis on problem solving and computation also makes it a strong foundation for postgraduate conversion courses and professional qualifications.

Why study at Swansea University

Swansea’s School of Mathematics combines teaching with active research across pure, applied and computational mathematics and statistics. Students benefit from small-group tutorials, access to modern computing facilities, and opportunities to work with staff on research-led projects. The School supports employability through careers workshops, placement opportunities and links with industry, while the campus and regional industry networks offer options for internships, study-abroad exchanges and a supportive learning community.

Whether you aim for a mathematically focused career or a role that uses quantitative skills, the BSc Mathematics at Swansea provides rigorous training and practical experience to prepare you for the next step.