COURSE CURRICULUM

The Python, AI, and Machine Learning for Financial Technology module (30 credits) aims to enhance Python programming skills while introducing students to AI theories and techniques. Students will learn to visualize data, apply AI and machine learning techniques to financial data, interpret results, and evaluate performance. The Advanced Software Development for Financial Technology module (15 credits) provides hands-on experience in software development, focusing on client-server technologies, databases, and APIs, which are essential in creating Financial Technology products.The Financial Markets and Data Analytics for Financial Technology module (30 credits) offers an overview of the operation of financial markets and their instruments. Students will critically examine case studies of Financial Technology products and become proficient in accessing and analyzing various types of financial data. The Current Topics in Financial Technology module (15 credits) allows students to engage with the cutting edge of the industry, where they will co-design learning activities and develop applications on areas of personal interest, either individually or collaboratively.The Mathematics and Blockchain Technology for Financial Technology module (30 credits) delves into the mathematics that underpin Financial Technology. Students will explore topics such as probability theory, calculus, and linear algebra, learning how these concepts are combined to develop powerful AI tools, data analysis techniques, hypothesis testing, and core financial models. Finally, the Financial Technology Project (60 credits) allows students to apply their knowledge and skills to a substantial independent or group project. In this module, students will demonstrate expertise in problem definition, research design, analysis, software development, and the critical presentation of results, potentially even prototyping their own Financial Technology product under the guidance of a supervisor.