COURSE CURRICULUM

The MSc in Financial Data Analytics combines advanced data science, finance, and quantitative analysis to prepare students for careers in the rapidly evolving financial sector. The program provides a strong foundation through core modules such as Computing for Data Analytics and Finance, Data Science Research Methods, Financial Portfolio Analysis, and Machine Learning. These modules develop essential skills in data processing, financial modelling, programming, and predictive analytics, enabling students to interpret complex financial data and make evidence-based decisions. Throughout the year, students also complete a Dissertation in Financial Data Analytics, applying theoretical knowledge to independent research or practical financial challenges. The course offers a range of optional modules that allow students to tailor their studies to their interests and career goals. Options include Algorithmic Data Science, Data Analysis Techniques, Financial Mathematics, Linear Statistical Models, Financial Investment and Corporate Risk Analysis, Machine Learning and Statistics for Health, Monte Carlo Simulations, and Statistical Inference. This flexibility ensures a well-rounded learning experience that integrates technical, analytical, and financial expertise. Graduates emerge with the ability to apply data-driven approaches to solve real-world financial problems, making them well-suited for roles in quantitative finance, risk analysis, data science, investment management, and related fields.