This module equips students with the tools to successfully analyse data, along with the theoretical and practical knowledge of computational methods used in the financial services industry. The module introduces students to programming with Python and highlights the usefulness of programming for data analytics. The module begins with an overview of various data types/structures. It then covers topics such as mathematical and logical operators, flow control, exception handling, functions, data exploration, and data wrangling. Following on from the foundations of data analytics, students focus on computational methods. These include series expansion, root-finding, optimisation methods, interpolation techniques, quadrature, and simulation methods. The lectures introduce key concepts while the seminars are more practical. The seminar/lab sessions provide students with the opportunity to apply their knowledge to extract and analyse data, as well as utilising computational methods using Python. Overall, the students will develop a range of skills, including communication skills, IT literacy, numeracy skills, and problem-solving skills.