COURSE CURRICULUM

The Master of Data Science requires the completion of 160 credit points and is structured to provide students with a strong theoretical foundation alongside extensive practical experience across the key areas of modern data science. Students complete 140 credit points of core units that develop skills central to data-driven problem solving, analytical reasoning and professional practice. These units cover essential topics such as foundational data science concepts, software systems, database design, advanced data management, business intelligence, IT service management, and risk and reliability management. Students also gain competence in data analytics, visualisation techniques, machine learning, artificial intelligence, and the principles of operating systems, networks and cybersecurity, all of which are critical to managing and interpreting large and complex datasets. Additional units focus on professional issues in technology and the practical integration of software and data systems, ensuring graduates understand the ethical and organisational implications of their work. A major component of the course is PRT661 Data Science Practice, a 20-credit point unit that consolidates learning through applied industry-embedded or practice-based experiences, encouraging students to engage with real-world challenges and develop professional competencies that enhance employability. To complement the core requirements, students choose one 20-credit point specialist elective that allows them to either gain workplace experience or undertake a research-focused thesis. PRT604 Professional Experience provides hands-on industry engagement, enabling students to apply their knowledge in professional settings and further develop practical skills. Alternatively, PRT840 IT Thesis offers the opportunity to complete a research project under academic supervision, ideal for those interested in contributing to the field through scholarly investigation or considering future research pathways. The overall course structure ensures a balanced blend of theory, technical capability, practical application and professional development, preparing graduates for multidisciplinary careers across technology, business, government, research and other data-intensive domains.