Capital University

What you'll study

This programme builds a strong foundation in pure and applied mathematics while emphasising computational methods and scientific programming. In early years you study core topics such as calculus, linear algebra, discrete mathematics, mathematical proofs and introductory programming. Middle years introduce numerical analysis, ordinary and partial differential equations, probability and statistics, algorithms and data structures, and optimisation.

• Foundations: single- and multivariable calculus, linear algebra, mathematical reasoning and proof techniques
• Computational core: numerical methods, scientific computing, numerical linear algebra, error analysis
• Applied modelling: differential equations, mathematical modelling, dynamical systems and simulations
• Data and algorithms: probability and statistics, computational statistics, algorithms, complexity and data structures
• Advanced options: computational geometry, numerical PDEs, optimisation and control, high-performance computing, machine learning
• Project and practical work: laboratory and computing practicals, group projects, and a substantial final-year individual or team capstone project focused on a computational problem

Teaching is typically delivered through lectures, seminars, computer lab sessions and project supervision. Assessment methods include written examinations, coursework, programming assignments and project reports.

Entry requirements

Applicants should demonstrate strong mathematical ability. Typical entry routes include A-levels (or equivalent) with mathematics strongly recommended; many students present further mathematics where available. International Baccalaureate entrants usually require higher level mathematics. Admissions also consider applicants with strong performance in relevant quantitative subjects such as physics, computing or statistics.

• Evidence of competence in mathematics at school level is essential.
• Some computing experience or familiarity with programming is helpful but not always mandatory; introductory modules support students new to coding.
• Mature students or those with alternative qualifications are considered on their academic merits and relevant experience.
• All applicants must meet the university's general admission criteria, including English language requirements for international students.

Career prospects

Graduates with a computational mathematics degree are well placed for a wide range of careers that value quantitative analysis and computational skill. Typical career paths include data science and analytics, software and systems development, quantitative roles in finance (such as risk or pricing analyst), scientific computing in engineering and research, operations research, and technical consultancy.

• Data scientist / data analyst
• Software engineer or developer (particularly in scientific and technical domains)
• Quantitative analyst in finance and insurance
• Research assistant or further study (MSc/PhD) in applied mathematics, computational science or machine learning
• Roles in modelling and simulation for engineering, environmental science and industry
• Teaching and outreach in mathematics and computing

Employers value the combination of rigorous mathematical thinking, practical programming experience and project work. The degree also provides a strong foundation for postgraduate study and professional conversion programmes.

Why study at Capital University

Capital University offers a supportive environment with small-group teaching and access to computing facilities tailored for scientific computing and data analysis. The mathematics department emphasises close supervision for final-year projects and opportunities to work on interdisciplinary problems with other departments, such as computer science, engineering and economics.

• Practical computing labs and software resources for numerical simulation, data analysis and high-level programming languages commonly used in industry and research.
• Opportunities for work placements, industry projects and collaborations that help develop employability and applied experience.
• Dedicated academic support, career services and a community of mathematics students engaged in societies, competitions and outreach.

The programme is designed to produce graduates who can bridge the gap between abstract mathematics and real-world computational challenges, preparing them for technical careers or advanced study.