Advance your knowledge in data analytics with the Master of Data Science. This program is designed for postgraduate students aiming to extract meaningful insights from diverse data sources. You will develop skills in cutting-edge techniques and learn contemporary tools relevant to the data management lifecycle. Upon graduation, you will be equipped to work at the forefront of data-driven decision-making and forecasting.
To qualify for the Master of Data Science, students must complete 200 credit points, comprising twelve (12) core units (175 credit points) and two (2) electives (25 credit points).
Graduates will be skilled to work at the forefront of data-driven decision-making and forecasting.
Meeting minimum entry requirements does not guarantee an offer. Credit transfer and Recognition of Prior Learning (RPL) are assessed on a case-by-case basis.
Fees are estimates for 2026 and are subject to change. Fees are assessed based on actual study load per semester. International student fees generally include the Student Services and Amenities Fee (SSAF).
Australian Computer Society
The yearly tuition fee for international students is $34,610.00 AUD, making the total fee for the two-year program $69,220.00 AUD. These are estimates for 2026 and are subject to change.
You need an IELTS Academic overall band score of 6.5, with no individual band below 6.0. Alternatively, you can provide proof of English for Academic Purposes (EAP 5 Advanced) with an overall score of 70% and all skills at 65% or above.
The program requires the completion of 200 credit points, which is typically structured over two years, encompassing graduate certificate, graduate diploma, and master's degree components.
Entry requires a Bachelor's degree (or higher) in any discipline from a recognised institution, or a Graduate Certificate or Diploma in Data Science. Successful completion of Swinburne's Postgraduate Qualifying Program is also accepted.
Graduates are skilled to work as a Statistician, Business Analyst, Data Engineer, or Data Architect, contributing to data-driven decision-making and forecasting.
Yes, students with a credit average are eligible to apply for an internship project unit (ICT80004) which provides practical experience.