COURSE CURRICULUM

The MSc Behavioural Economics and Data Science is a 12-month program that equips students with a comprehensive understanding of economic theory, behavioural insights, and data analysis. It begins with a pre-sessional course in September, followed by core training in microeconomics, macroeconomics, and econometrics during the autumn semester. Students also gain hands-on skills in programming and analytics, particularly in Python, focusing on tasks like web scraping, data cleaning, and exploratory data analysis. In the spring semester, students choose from a range of specialist modules, such as Behavioural Consumer Analytics and Data Mining, which explore consumer decision-making and practical data science applications. The course places strong emphasis on quantitative methods and practical experience with tools like STATA and Python libraries such as Pandas and Scikit-learn. Dissertation preparation starts in the spring, with training in topic selection, data sourcing, and referencing. The dissertation itself is undertaken in the summer and may be based on independent research or in collaboration with an external organisation, giving students the chance to apply their skills to real-world economic or policy problems. Throughout the year, students learn how to critically engage with economic and behavioural theories, analyse data effectively, and understand how behavioural insights influence consumer decisions and public policy. This multidisciplinary approach ensures that graduates are well-prepared for careers in consultancy, policy analysis, market research, or further academic study.