COURSE CURRICULUM

The MSc Economics and Data Science program combines advanced training in economic theory with practical skills in data science, preparing students for careers in economic analysis, policy, and research. Core modules, including Microeconomic Theory, Macroeconomic Theory, Introduction to Quantitative Methods in Economics, and Econometric Methods, provide a strong foundation in economic principles and quantitative analysis. Data Science and Machine Learning 1 and 2, along with Programming and Other Skills for Data Scientists, equip students with practical expertise in programming, machine learning, and computational techniques essential for analysing complex economic data. The Dissertation allows students to undertake an extended, independent research project, applying both economic theory and data science methods to real-world problems. Optional modules, such as Microeconometrics and Financial Econometrics, enable students to specialise in areas of econometric analysis and financial data applications. The program emphasizes hands-on, practical learning and the integration of economic theory with empirical methods, developing skills in problem-solving, data interpretation, and critical thinking. Graduates leave with a combination of strong theoretical knowledge, quantitative expertise, and applied research experience, making them highly employable in diverse sectors, including government, central banks, financial institutions, consultancy, and academia, where they can use data-driven insights to inform economic decision-making, policy evaluation, and strategic planning.