COURSE CURRICULUM

The Master of Health Data Analytics requires completion of 96 credit points, structured across three key components: Part A Foundation studies (54 credit points), Part B Applied studies (24 credit points), and Part C Discipline studies (18 credit points). The Foundation studies provide the core knowledge and skills required for health data analytics, including essential areas such as programming, biostatistics, epidemiology, mathematics, and data science principles. This stage builds a strong base in both health sciences and quantitative methods, ensuring students understand how to interpret and manage complex health datasets. The Applied studies component focuses on the practical application of these skills to real-world health problems, enabling students to work on data-driven projects such as modelling patient outcomes, evaluating treatment effectiveness, and developing machine learning solutions for healthcare challenges. This stage emphasises hands-on experience, problem-solving, and the use of advanced analytical tools. The Discipline studies component allows students to deepen their expertise in specialised areas of health data analytics, such as biostatistics, machine learning, or related fields, depending on their chosen focus. Together, these three components create a comprehensive and integrated learning pathway that combines theory, practice, and specialisation. Overall, the 96-credit-point structure prepares graduates to become skilled health data professionals capable of contributing to healthcare innovation, research, and data-driven decision-making in global health systems.