Computer Science and Mathematics

Durham University

Taught by discipline specialists and informed by industry, this course brings together the complementary fields of computer science and mathematics, and offers opportunities to specialise and apply your learning in practical ways.,In our changing world, the field of computer science which is underpinned by mathematics is a driving force behind many of the transformative technological breakthroughs that have shaped our lives. The skills required by today's dynamic tech sector demand a robust knowledge of mathematical fundamentals, statistics and machine learning. The BSc in Computer Science and Mathematics allows you to explore the connections between the two fields and provides the foundational knowledge and practical skills needed to thrive in a data-driven workplace. At Durham, learning is informed by our close collaborations with high-tech industries and employers, which affords us invaluable insights into emerging trends and priorities in the industry. The wide array of option modules provides the flexibility to tailor your learning in line with your evolving interests. In addition, the common first year allows the option to transfer onto either the MSci Computer Science and Mathematics, BSc Computer Science, BSc Mathematics degree or BSc Natural Sciences at the end of Year 1. A degree in Computing and Mathematics opens doors to a wide range of exciting roles where you can make a real difference in the world. And in this fast-evolving field, you're not just preparing for the jobs that exist today, you’re also equipping yourself with the skills to thrive in new and emerging areas.An equal balance of Computer Science and Mathematics in Year 1 includes computer science, pure mathematics, statistics and probability, before moving on to a range of option modules in innovative technological applications during Year 2. This provides a strong foundation from which you can explore more advanced topics in statistics, artificial intelligence and data science in the final year. The final year also includes an individual project and the option to complete our interdisciplinary enterprise module. This module develops complementary graduate skills as you work in groups to develop a business plan to bid for mock research funding.Course structureYear 1 modulesCore modules:Computational Thinking explores the breadth of computer science and the ways in which the different topics are linked. You will learn the importance of computation and computational thinking in the modern world and the impact it has on technology advances in different settings.Algorithms and Data Structures introduces the theory and practice of problem-solving in computing through the development of algorithms and their associated data structures, for common computer science problems. Content included machine modelling, control flow structures and analysis of algorithms.Calculus builds on ideas of differentiation and integration in A level mathematics. The module begins with functions of a single variable before moving on to functions of several variables. Topics include methods of solving ordinary and partial differential equations, and an introduction to Taylor series, Fourier series and Fourier transforms.Linear Algebra presents mathematical ideas, techniques in linear algebra and develops the geometric intuition and familiarity with vector methods you will need for more challenging material later in the course.Probability introduces mathematical ideas on probability in preparation for more demanding material later in the course. The module builds problem solving skills through the exploration of a mathematical subject of relevance to the real-world (applied) that is based on rigorous mathematical foundations (pure).Statistics introduces frequentist and Bayesian approaches and demonstrates the relevance of these principles and procedures using real problems. This introductory module lays the foundations for all subsequent study of statistics.