COURSE CURRICULUM

The MSc Finance and Data Analytics program is designed to equip students with a robust understanding of financial markets while integrating advanced data analytics and quantitative methods. The course begins with foundational training in research methods and postgraduate mathematics preparation, ensuring students develop the technical skills necessary to handle complex financial data. Core modules include big data in finance, which focuses on analysing and interpreting large datasets from multiple sources, and portfolio management, where students learn to construct, monitor, and optimise investment portfolios. The curriculum also covers financial time series methods and applications, providing expertise in modelling and forecasting financial variables over time, as well as data analysis techniques for cross-sectional, panel, and qualitative data, allowing students to draw meaningful insights from diverse financial datasets. Students are encouraged to apply these skills in their dissertation, an extended independent research project that synthesises analytical, statistical, and financial knowledge in a real-world context. Optional modules allow further specialisation, tailoring the degree to individual career goals. Throughout the program, professional and academic development support ensures students are prepared for the financial services industry, with competencies in data-driven decision-making, quantitative finance, and modern analytical techniques. Graduates emerge with the ability to combine financial theory, empirical research, and advanced data analysis, positioning them for specialist roles in investment management, risk analysis, and financial consultancy in an increasingly data-centric sector.