COURSE CURRICULUM

The MSc Digital Finance and Data Analytics programme provides a comprehensive curriculum that combines financial expertise with advanced analytical and technological skills. Students begin by studying Global Financial Markets, gaining an understanding of the structure, operation, and dynamics of international financial systems and institutions. Introduction to Programming and Data Analytics for Finance and FinTech develops essential coding and data analysis skills, enabling students to work effectively with financial datasets and digital technologies. Principles of FinTech explores the innovations transforming financial services, including digital banking, blockchain, cryptocurrencies, and financial technologies. Professional Practice in Finance enhances students’ understanding of professional standards, ethics, and career development within the finance sector. Advanced modules include Empirical Finance, which focuses on applying quantitative methods to analyse financial data and market behaviour, and Principles of Machine Learning in Finance, where students learn how artificial intelligence and machine learning techniques can support financial decision-making and forecasting. Contemporary Topics in Digital Finance examines emerging trends and challenges shaping the future of financial services, while Research Methods for Finance and Accounting develops the analytical and research skills required for evidence-based investigation. The programme concludes with a Consultancy Experience Project, providing students with the opportunity to apply their knowledge to real-world business challenges and financial datasets. Together, these modules develop strong technical, analytical, and professional capabilities, preparing graduates for careers in digital finance, FinTech, financial analytics, and data-driven financial services.