COURSE CURRICULUM

The MSc Economics and Data Science is a 12-month program beginning in September, structured around two semesters of coursework followed by a summer dissertation. Each semester includes three taught modules, covering core areas of economics along with specialized data science training. In the autumn, students take foundational modules in microeconomics, econometric theory, and programming using Python, learning essential skills like data cleaning, visualization, and policy evaluation techniques. These are complemented in the spring by applied econometrics, macroeconomic theory, and a focused data science module that extends knowledge from earlier coursework into machine learning and advanced data analysis within economic contexts. Practical use of tools like STATA and Python is emphasized throughout. Alongside these academic modules, students begin dissertation training in spring through lectures and workshops that guide them in topic selection, data access, literature review, and research design. Additional lab-based workshops in early summer offer hands-on experience in applying these skills. The dissertation, either academic or in partnership with an external organization, allows students to independently explore a topic of interest using the quantitative and analytical techniques learned during the course. This module, concluding in August, requires a detailed proposal and multiple supervisory meetings to refine the project. Overall, the course offers a strong combination of theoretical economics and practical data science skills, equipping students for careers or further research in areas that require both economic insight and data-driven decision-making.