COURSE CURRICULUM

The Master of Data Science is designed to develop highly skilled professionals equipped to meet the growing demand for expertise in data analytics, machine learning, and computational methods. The program structure balances core technical knowledge, applied practice, and specialised study. All students complete 75 points of core subjects covering essential statistical and computer science principles, 25 points of capstone subjects that involve a year-long practical research project, and 100 points of formal specialisation tailored to their background and interests. The capstone project allows students to work individually or in teams on real-world data science problems, presenting results in a client-ready format.Students’ prior experience determines their pathway. Those without a background in statistics or computer science may need to complete foundation subjects to meet the prerequisites for the core subjects. If students already meet the prerequisites or have completed a related graduate diploma or undergraduate data science major, they may be eligible for an accelerated 1.5-year program with up to 50 points of credit. Foundation subjects include statistics or computer science courses depending on students’ prior knowledge, ensuring that all students develop the fundamental skills necessary to progress into advanced data science study.The program offers four specialisation streams: Foundational Data Science, Statistical Data Science, Computational Data Science, and Computational and Statistical Data Science. Each specialisation combines core discipline subjects with elective subjects drawn from statistics, computer science, and professional skills, and may include internships or additional research projects. Students gain practical experience alongside theoretical knowledge, with opportunities to engage in 80–100-hour internships in science and technology workplaces. This approach ensures graduates are equipped with both the technical expertise and applied experience needed to pursue careers in data science, analytics, machine learning, or related roles in diverse industries. The program emphasises flexibility, industry engagement, and the development of transferable analytical and computational skills, preparing graduates to tackle complex problems in an increasingly data-driven world.