Master of Data Science (Professional)

To complete the Master of Data Science (Professional), you must pass 8, 12 or 16 credit points. The number required may vary depending on your entry point or how much credit you receive as recognition of prior learning (RPL) based on your professional experience and previous qualifications. A standard 16-credit-point program includes Part A (Fundamental Data Science studies), Part B (Mastery Data Science studies), Part C (Specialisation or course electives), and Part D (Professional studies).

The Master of Data Science (Professional) is available across three trimesters: Trimester 1 starting in March, Trimester 2 starting in July, and Trimester 3 starting in November. All three intakes are available at Burwood (Melbourne) and Online. Direct applications for Trimester 2 2026 close 21 June 2026, and for Trimester 3 2026 close 18 October 2026.

To be considered for admission, you need to meet at least one of the following academic criteria: completion of a bachelor degree or higher in a related discipline (such as Information Technology), or completion of a bachelor degree or higher in any discipline plus at least two years' relevant work experience. For English language proficiency, you need at least one of: a bachelor degree from a recognised English-speaking country, an IELTS overall score of 6.5 with no band score less than 6.0, or other accepted evidence of English language proficiency.

The estimated tuition fee for a full-fee paying place is $34,400 for 1 year full-time. For students in a Commonwealth Supported Place (CSP), the estimated tuition fee is $8,937 for 1 year full-time. These are guide figures only; actual costs will vary depending on the units you choose, your study load, the length of your course, and any approved Recognition of Prior Learning. HELP loans including FEE-HELP or HECS-HELP may be available depending on eligibility.

Students can choose from a range of specialisations as part of Part C of the course structure, including: AI and Computer Vision, Analytics in Internet of Things, Blockchain and Software Development, Business Analytics, Cyber Security, Information Systems, Information Technology, Research Training, and Networking and Cloud Technologies. Alternatively, students may select 4 credit points of course elective units at level 7 SIT or MIS-coded (excluding SIT771, SIT772, SIT773 and SIT774).