COURSE CURRICULUM

This master’s program explores the intersection of finance, digital technology, and innovation, preparing students for careers in modern financial services. It includes four 30-credit core modules and a final 60-credit project, either a dissertation or an internship.The Financial Services and Digital Banking module introduces students to the digital transformation of financial services. It explores emerging trends in FinTech, the role of challenger banks, and technologies like RegTech, using real-world case studies to illustrate modern banking innovations.Quantitative Methods and Python Programming provides practical experience in data science, focusing on Python programming for business and finance applications. Students learn statistical analysis, machine learning basics, and data visualisation techniques, building skills essential for data-driven decision-making.Applied AI and Machine Learning dives deeper into how artificial intelligence and machine learning are being used in finance. It covers various AI methods, the relevance of blockchain, and practical forecasting through machine learning models, helping students design and test AI projects.Entrepreneurship and AI Risk Management focuses on starting and managing AI-driven ventures. It blends entrepreneurial finance with AI risk management strategies, emphasising ethical AI practices and responsible innovation in a fast-moving tech environment.To complete the degree, students choose between a Dissertation or an Internship Project. The Dissertation involves independent research on a topic of interest, guided by a supervisor, aimed at generating meaningful insights. Alternatively, students can complete a nine-week industry internship, applying their knowledge in a practical setting while gaining professional experience. Both pathways are designed to consolidate learning and prepare students for the complexities of the financial and technological sectors.