COURSE CURRICULUM

The MSc in Data Analytics and Financial Technology is a three-semester interdisciplinary postgraduate programme that combines finance, data science, and emerging technologies to prepare students for careers in the rapidly evolving FinTech sector. In the first semester, students build a strong foundation through modules in accounting and financial statement analysis, research and quantitative methods in finance, problem-solving programming, and banking operations and management. These subjects develop essential skills in financial analysis, quantitative techniques, programming, and understanding modern banking systems. The second semester focuses on advanced technological applications in finance, including blockchain and cryptocurrencies, modelling high-frequency finance, and data analytics, enabling students to analyse large datasets and understand the technological innovations transforming financial services. Students can also choose electives such as disruptive technologies and trading strategies and applications, allowing them to specialise in areas related to digital transformation, algorithmic trading, and emerging financial technologies. The programme concludes in the third semester with a dissertation, where students conduct independent research and apply analytical and technical skills to solve real-world problems in finance and technology. For applicants who do not possess sufficient prior knowledge in finance or data analytics, foundation courses may be offered to ensure they are adequately prepared for the programme's interdisciplinary nature. Overall, the degree is designed to develop highly skilled professionals with expertise in big data, financial technology, programming, and quantitative finance. By integrating theoretical concepts with practical applications, the programme prepares graduates for careers in banking, financial analytics, investment management, fintech companies, and data-driven business environments, while also providing a strong academic foundation for further research and doctoral studies in finance, data science, and financial technology.