COURSE CURRICULUM

The MSc Economics with Data Science is structured to provide students with strong foundations in economics, econometrics, and computational methods, while also offering flexibility to specialise in areas of interest. Core training begins with modules in Microeconomics and Econometric Methods, each worth 20 credits, which develop theoretical and empirical skills essential for analysing economic behaviour and data. Data Science for Economics further enhances students’ ability to process and interpret large datasets, equipping them with modern computational techniques that are increasingly vital in research and industry. The program also includes a dissertation worth 40 credits, where students independently investigate a chosen topic, applying both economic theory and data science skills to produce original research. Flexibility is provided through compulsory-with-options modules, including choices among EC964-7-SP, EC965-7-SP, or EC968-7-SP, as well as between EC969-7-SP or CF969-7-PT, enabling students to align their studies with their academic or professional goals. In addition, students select 40 credits from a wider list of optional modules, allowing further customisation in fields such as finance, macroeconomics, or applied econometrics. Together, these components deliver a comprehensive training program that integrates economics and data science, preparing graduates for careers in policy, business, finance, or further academic research.