COURSE CURRICULUM

The Master of Science in Financial Analytics provides a structured and comprehensive curriculum designed to build strong competencies in finance, data analytics, and emerging technologies. In Stage One, learners are introduced to the core foundations of finance and data analysis through modules such as Principles of Financial Decision Making and Data Analytics & Machine Learning for Finance. These are followed by modules like Predictive Financial Modelling and Applied Financial Analytics, which equip students with practical skills in forecasting and using analytical tools to solve real-world financial problems. Financial Intelligence & Data Visualisation helps students understand and present complex data insights effectively, while Information & Cybersecurity Management provides critical awareness of protecting financial systems in a digital environment.Additionally, students explore Financial Risk Management to understand how to identify and mitigate financial risks, and Behavioural Economics & Finance, which examines how psychological factors influence financial decision-making. The Innovation in Financial Technology module addresses the impact of digital advancements such as blockchain, digital currencies, and fintech solutions on the finance industry.Stage Two focuses on research development and application. The Applied Research Methods module prepares students for conducting structured academic or industry-related research, culminating in the Applied Research Project. This final component allows learners to demonstrate their ability to apply theoretical knowledge to practical challenges in financial analytics.