COURSE CURRICULUM

The Financial Data Science MSc offers a rigorous and industry-focused program that equips students with the advanced knowledge and practical skills required to succeed in the intersection of finance, data science, and artificial intelligence. In the first semester, students develop a strong foundation in artificial intelligence and financial informatics, gaining the technical expertise to analyse and manage complex financial data. Core modules cover financial markets and derivative pricing, providing essential insights into market dynamics and instruments, alongside an in-depth study of derivatives markets. Optional modules such as Bayesian inference for data sciences, fundamentals of blockchain, and advanced quantitative methods in economics allow students to tailor their learning to specific interests and emerging technologies in finance. The second semester builds on these foundations with modules in principles of data science, mathematics of data science, and data-driven methods, enabling students to apply computational techniques, statistical analysis, and predictive modelling to financial datasets. Further optional modules include machine learning methods and big data, as well as mathematical time series, supporting advanced analytical applications. Across the academic year, students undertake a dissertation project, integrating theory, quantitative methods, and practical research to solve real-world financial problems. This comprehensive approach ensures graduates are highly employable and ready to contribute to roles in financial analytics, risk management, algorithmic trading, and data-driven decision-making.