COURSE CURRICULUM

The Master of Data Science program is structured as a 160-credit-point degree designed to provide a strong balance of core technical training, analytical thinking, and flexible specialization options. The core component consists of 120 credit points and includes essential subjects that build foundational and advanced skills in programming, mathematics, statistics, and data analysis. Students study key units such as Programming for Data Science, The Nature of Data, Big Data, Data Science, Visualisation, Advanced Statistical Methods, Predictive Analytics, Social Media Intelligence, Probabilistic Graphical Models, Advanced Machine Learning, and structured postgraduate project work through Project A and Project B. These subjects ensure that students develop strong capabilities in handling complex datasets, applying statistical models, and using machine learning techniques for real-world problem-solving. In addition to the core, students complete 40 credit points of electives, which allow them to broaden or specialise their knowledge depending on career goals. These electives can be chosen from across the university, subject to prerequisites, and may be used to complete a suggested major. Specialisation options include testamur majors such as Artificial Intelligence, Cybersecurity, Digital Health, Public Health, or various business-related majors like Finance, Marketing, Management, Innovation and Entrepreneurship, and Logistics and Supply Chain Management. Overall, the structure ensures graduates are well-prepared for diverse careers in data science, analytics, AI, and related interdisciplinary fields.