BSc Mathematics with Computer Science
About this course
Mathematics and computer science are among the most naturally allied disciplines in the university curriculum: computer science as a formal discipline is grounded in mathematical logic, discrete mathematics, probability and algebra, and the most powerful work in computing consistently draws on deep mathematical understanding. Conversely, mathematics has found some of its most productive new directions in computational questions, from algorithms and complexity theory to the mathematics of machine learning and cryptography. Studying both together gives you something that neither degree alone provides quite so cleanly: genuine mastery of the formal foundations alongside the practical skills to build and use computational systems. At Brunel University London, this programme is designed on exactly that logic, as the university notes: mathematics is the language of computer science, and students who are fluent in both have access to a wider range of careers than those trained in only one. The degree includes a foundation year, providing supported entry for students who need to consolidate their mathematical and scientific background before engaging with degree-level material. You will study pure and applied mathematics, statistics and numerical methods alongside programming, algorithms, data structures, software engineering, computer architectures and computational problem-solving. The combination develops both rigorous analytical thinking and practical implementation skills. The foundation year allows the programme to be genuinely accessible to students who might not have the strongest prior record, while the main degree is intellectually demanding and prepares you for challenging roles. Graduates go on to careers in software engineering, data science, mathematical modelling, cybersecurity, quantitative finance, research computing, systems analysis and technology consulting across a very wide range of sectors. The mathematical rigour the degree develops is a significant advantage in roles that require working with complex data or building reliable software systems. Further study in computer science, mathematics, data science or related fields is also a well-established route.
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