Mathematics with Data Science, MSci (Hons), with industry placement

This MSci in Mathematics with Data Science provides comprehensive training in analytical and quantitative skills, blending practical mathematics and data science to prepare graduates for diverse careers in industries like finance, technology, and research. It fosters critical thinking and advanced techniques, such as machine learning and cryptography, while emphasizing universal mathematical principles and real-world applications. Students gain employability through optional work placements and career-focused modules, exploring topics from calculus to artificial intelligence via individual and group projects.The four-year program features core modules in the first two years, including functions, algebra, and programming, with greater flexibility in later years for subjects like differential equations and deep learning. Assessment combines examinations, coursework, and projects, weighted across years, with timely feedback to support student development.

This four-year MSci Mathematics with Data Science degree is focused on pure mathematics with real applications. As you progress, you will have increasing choice and flexibility about what you choose to study. Year 1 consists of modules that make up 125 credits. All modules are core. -Functions, Vectors and Calculus (30 credits) -Algebra (15 credits) -Linear Algebra (15 credits) -Introduction to Probability and Statistics (15 credits) -Logic and Set Theory (15 credits) -Number Theory and Cryptography (15 credits) -Introduction to Modelling (15 credits) -Skills, Careers and Employability Analysis for Mathematics students (5 credits) Year 2 consists of modules that make up 125 credits. -Programming and Data Science for the Professions (15 credits) -Real and Complex Analysis (30 credits) -Vector Calculus (15 credits) -Sequences and Series (15 credits) -Decision Analysis (15 credits) -Applied Mathematics (15 credits) -Numerical Mathematics (15 credits) -Professional Development and Employability (5 credits) -Applications of Probability and Statistics (15 credits) Year 3 consists of modules that make up 120 credits. -Codes (15 credits) -Techniques for Data Science (15 credits) -Group project (15 credits) -Principles of Data Science (15 credits) Introduction to Artificial Intelligence (15 credits) -Machine Learning (15 credits) -Differential Equations (30 credits) -Advanced Complex Analysis (15 credits) -Stochastic Models (15 credits) -Operational Research (15 credits) -Probability and Statistics 2 (30 credits) -Graph Theory (15 credits) -Game Theory (15 credits) -Dynamical Systems (15 credits) -Introduction to the Mathematics of Fluids (15 credits) -Introduction to Mathematical Physics -Mathematical Processes for Finance (15 credits) -Groups and Symmetry (15 credits) -Mathematical Biology (15 credits) Year 4 -MSci Project (30 credits) -Mathematics: algorithms, computation and experimentation (15 credits) -Machine Learning (15 credits) -Data Visualisation (15 credits) -Deep Learning (15 credits) -Principles of Data Science (15 credits) -Introduction to Artificial Intelligence (15 credits) -Mathematics for Quantum Computing (15 credits) -The Mathematics of Information (15 credits) -Forecasting (15 credits) -Perturbation Methods (15 credits) -Game Theory (15 credits) -Graph Theory (15 credits) -Dynamical Systems (15 credits)