COURSE CURRICULUM

The MSc Data Science (Mathematics) program provides a comprehensive education in advanced quantitative methods, statistical analysis, and computational techniques, preparing students for careers in data-driven fields. Core modules such as Statistics and Machine Learning 1: Statistical Foundations and Statistics and Machine Learning 2: AI, Complex Data, Computationally Intensive Statistics develop students’ expertise in statistical modelling, machine learning, and handling complex datasets. Understanding Databases and Understanding Data and their Environment equip students with essential skills in data organisation, management, and contextual interpretation, while Applying Data Science focuses on translating theoretical knowledge into practical problem-solving using programming tools such as R, Python, and Excel. The Extended Research Project allows students to undertake an independent, supervised study, integrating computational and mathematical techniques to address real-world challenges. Optional modules, including Computation and Complexity, Introduction to Uncertainty Quantification, Linear Models with Nonparametric Regression, and Time Series Analysis and Forecasting, enable students to specialise in areas such as algorithmic analysis, predictive modelling, and advanced statistical methods. The program combines rigorous mathematical training with applied data science skills, fostering analytical thinking, problem-solving, and professional competence. Graduates are well-prepared for careers in business, policy, research, consultancy, and other sectors requiring expertise in data analysis, modelling, and evidence-based decision-making.