Top 3 Online Data Science Masters in Australia
A data science masters sets up your career by consolidating prior learning and filling knowledge gaps. Here are Australia’s best programs.
Excel as a data scientist by completing one of the best master’s programs online.
The top data science masters in Australia share some things in common. The courses are 100% online and give the option for part-time study, meaning no time away from work is needed. Build skills in artificial intelligence, database management, analytics, data visualisation, machine learning, and more.
UNSW Online – Master of Data Science
The 100% online Master of Data Science at UNSW explores how to organise, identify, analyse and use data to inform strategies, redefine ambiguous questions, and find impactful answers. You can focus on areas such as machine learning, database systems, and decision making.
- Ranked 1 for Median Graduate Income*
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The UNSW data science program is designed to develop sought-after capabilities for immediate use. You will be in demand for diverse roles (even those yet to be imagined), creating a dynamic and rewarding career. Delivered in 7-week intensive blocks, one course at a time, you can graduate in as little as two years studying part-time.
Machine Learning at UNSW
Machine learning happens when data scientists apply tools and techniques that allow computers to learn from data. It requires statistical methods plus techniques for producing artificial intelligence. Machine learning is an area you can concentrate on at UNSW with subjects that include Data Mining and Machine Learning; Neural Networks and Deep Learning; and Bayesian Inference and Computation.
Griffith University – Master of Data Science
Griffith’s Master of Data Science is for IT graduates as well as career changers. The course covers data analytics, machine learning, artificial intelligence, and big data technologies, with options to study advanced areas such as deep learning and natural language processing.
- Ranked 1 for Full-Time Employment*
- Ranked 1 for Graduate Satisfaction*
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The trimester-structured degree exposes participants to data science tools and technologies including Python, SQL, Hadoop, Tableau, and machine learning frameworks. Students can undertake industry projects and optional placements with external organisations.
Flexible Entry Pathways
One distinctive feature of Griffith’s program is the range of entry options. Students with an IT background may complete the degree in 1 year full-time, while applicants from unrelated disciplines can enter through a 2-year pathway that includes foundation studies in programming, databases, and statistics.
Deakin University – Master of Data Science
Deakin’s Master of Data Science is professionally accredited by the Australian Computer Society. The course includes foundation IT, data analytics, mastery data science, and capstone studies.
- Above-average for Graduate Satisfaction, Full-Time Employment, and Median Salary.
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Deakin lists specialist units such as Machine Learning, Bayesian Learning and Graphical Models, Deep Learning, Data Wrangling, Statistical Data Analysis, and Modern Data Science. The degree is available online or at Burwood, with intakes in March, July, and November.
Capstone and Industry Options
The course includes a two-part capstone sequence: Team Project (A) – Project Management and Practices, followed by Team Project (B) – Execution and Delivery. Students can also choose to undertake an industry placement or internship as part of the degree.
* Ranking Method
The rankings of data science programs derive from a combination of two main sources: The Graduate Outcomes Survey (GOS) and the Student Experience Survey (SES).
- The GOS targets recent graduates from Australian higher education institutions. It provides insights into employment outcomes and the relevance of skills in the workforce. Annually, it gathers responses from over 130,000 graduates across various study levels.
- The SES assesses the current higher education student experience in Australia. It evaluates measurable aspects linked to learning outcomes that institutions can influence. It surveys over 175,000 undergraduates and 65,000 postgraduates annually.
For data science programs, we focused on responses within the broader field of Computing and Information Systems (postgraduate) from both surveys. The final list was limited to universities offering an online master’s program in data science.
UNSW ranked first due to its outstanding performance in employment outcomes and median salary. Griffith was ranked second, performing exceptionally in graduate employment and course satisfaction.
Deakin’s inclusion in the top three is partly because of industry connections in the age of AI. With data science evolving alongside AI, courses with reduced theoretical or technical content may become increasingly relevant.
Graduate Certificate in Data Science
A useful pathway to a data science master’s is an online Graduate Certificate in Data Science. The course consists of four subjects from a master’s program and normally has lower entry requirements. It is a way to both test out and qualify for a master’s program.
This certificate develops essential data science skills. Topics cover artificial intelligence, consumer analytics, machine learning, etc. It’s designed for those looking to pivot their career into the field or enhance their current role with data-driven decision-making skills.
Completing a grad cert can significantly boost your career. It offers a postgraduate qualification in a growing field, with options to progress to a graduate diploma or master’s. This course suits anyone aiming to advance in the tech-driven job market without pausing their career.
Related: Graduate Certificate in Data Science Online
Is Masters Enough to Be a Data Scientist?
For many people, a data science master’s degree is sufficient to become a data scientist. This is especially true if you follow our roadmap for how to become a data scientist, which includes gaining relevant job experience as an intermediate step.
Before undertaking your master’s, you could, for example, gain experience as a data analyst, analytics manager, data engineer, or AI engineer.
Without experience, you might struggle to find a job opening even with a master’s degree. Employers are looking for candidates with relevant experience who can hit the ground running.
To address the problem of inexperience, building a data science portfolio is an effective solution.
- Complete projects such as data visualisation projects, machine learning models, or analysis of real-world data sets.
- Choose activities that align with job requirements for the positions you’re targeting.
Showcasing these projects in your portfolio can significantly enhance your job prospects. They are tangible evidence of your capabilities.
What Graduates Have to Say
Richard Shanahan, Chief Solutions Officer at Tiimely, found that a Master of Data Science gave him adaptable skills. He explains, “Throughout the course, you’re building tools and models that you can adapt to various situations. That forms part of a data science toolkit that you can take away.” This toolkit empowered Richard to drive data strategy and product development, solving challenges in the tech industry.
Lachlan Sharp, Senior Data Specialist at ConocoPhillips, credits his Master of Data Science for opening new career paths beyond traditional engineering. “Data is universal, and a lot of businesses are looking for people with experience in data science,” he says. The flexibility of online study allowed Lachlan to balance work, family, and education. He adds, “The real joy is being able to use what I learn in my workplace.”
Online postgraduate studies in computing boosted the career of Gavin McDonald, a Build and Systems Administrator at The Apache Software Foundation and former owner of 16degrees.com.au. His expertise in data science helps him manage infrastructure and support over 300 global open-source projects. Gavin notes: “The advanced skills I gained, especially in data management and automation, apply to my daily work.”
