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 accelerated. Part-time study means no time away from work is needed. Build skills in artificial intelligence, database management, analytics, data visualisation, machine learning, and more.
1. 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 Graduate Employment.*
- Ranked 1 for Median Graduate Income.*
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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.
The 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.
2. JCU Online
Master of Data Science
James Cook University has a flexible degree for launching a successful data scientist career. You can start with a 4-subject graduate certificate, before moving on to a graduate diploma (8 units) or the full Master of Data Science (12 - 16 units).
- Ranked 1 for Support Services.*
- Ranked 1 for Interactions with Staff and Students.*
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Applied Learning at JCU Online
Applied data science programs emphasise the development of job-ready skills. Students work with messy data sets, using the same software and tools that leading data scientists use in the field today. At JCU, you’ll learn visualisation tools such as SAS and Tableau, software development platforms like R-Studio and Jupyter, and gain experience on cloud computing platforms including AWS. Students build a portfolio to demonstrate expertise.
The program is affordable and easy to manage. Topics include data visualisation, database systems, machine learning, and big data. You can also study for a Graduate Diploma of Data Science (Internet of Things), exploring the use of data from internet-connected devices and sensors.
3. RMIT Online
Master of Data Science Strategy and Leadership
Top companies are looking for "data connectors" who have excellent communication as well as technical skills. Technical competence has limited value if you can't convert that ability into real impact. This program is about producing high-value graduates with management skills.
- Open to Business graduates, not just IT.
- Capitalise on AI by leading innovation.
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Strategy and Leadership at RMIT Online
This degree is designed for business professionals who want to connect data analysis with company objectives. Australian businesses desperately need managers able to skilfully organise the efforts of data professionals. Learn how data processes work from a technology manager's perspective with a program focusing on strategic management. Coding experience is not essential.
The 100% online degree consists of 12 seven-week subjects. You can study year-round while working full-time. Topics include shaping organisations with artificial intelligence, practical data science, consumer analytics, and machine learning for decision makers.
* 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. JCU was ranked second, partly because of its highly rated support services.
RMIT's inclusion in the top three pertains to its focus on strategy, leadership, and innovation in the age of AI. With data science evolving alongside AI, courses with reduced techhnical 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.