A data science masters degree can set up your career in this field by consolidating prior learning and filling knowledge gaps. Here are the best online courses in Australia.
Data science is a rapidly growing field presenting enormous career opportunities. An excellent way to build a knowledge base is with postgraduate courses. Students learn how to skilfully use big data to inform business decisions.
Become an expert data scientist or data science manager with a comprehensive training program. Online courses are designed for busy people and many students are working professionals. You can study with your choice of Australian university.
Specialisations
Best Data Science Masters in Australia
The best data science masters in Australia share some things in common. All the courses listed here are 100% online and accelerated, which means year-round study at convenient times. The programs are also offered part-time, with subjects completed sequentially across 6-8 week study blocks.
An online degree from an Australian university allows you to build high-level skills in database management, data wrangling, analytics, programming, data visualisation, machine learning, artificial intelligence, and the list goes on.
Applied Data Science
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. The idea of the applied course is to limit theory, allowing more time to be spent building industry-relevant skills and learning by doing.
University of Adelaide
If you have a degree of any kind, you have the opportunity to become a data scientist with the University of Adelaide's Master of Data Science (Applied). The flexible, 100% online degree will have you extracting useful information from real-world datasets with Python and R. Students learn how to apply leading-edge tools and methods, meet industry demands and communicate with clients. Each subject in the 12-16 unit program takes just 6 weeks of study using an intuitive online platform. The program aims to produce graduates who are able to make an immediate impact.
General Programs
A general program in data science aims to provide comprehensive training. Coursework allows students to build all the essential knowledge and skills required for a career in this field.
James Cook University
James Cook University has a flexible degree for launching a successful data science 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). The program is affordable and easy to manage. You're able to focus on one subject at a time and study year-round. Topics include data visualisation, database systems, data mining and machine learning, big data, and strategic decision making.
UNSW Online
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 specialise in areas such as machine learning, database systems or statistics. 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.
Internet of Things (IoT)
If you're looking to pick up some specialist skills, you can focus on the Internet of Things (IoT) as part of your postgraduate coursework. Students explore the use of data generated from internet-connected devices and sensors. This is a growth field that you can get into early with university-level training.
James Cook University
Specialised training in the Internet of Things (IoT) is available as part of the popular data science program at James Cook University. JCU offers an 8-subject Graduate Diploma of Data Science (Internet of Things), including the option of a 4-subject graduate certificate and continuation for a general masters. Topics include IoT communication technology, a hands-on look at sensors and their embedded computing systems, and cloud computing security. Students complete each subject as part of a virtual class over a 7-week teaching period. To be admitted, you should have a strong background in one or more STEM fields.
Machine Learning
Machine learning happens when data scientists apply tools and techniques that allow computers to learn from data. You can build strong machine learning skills with a program containing extra content in this field. Students learn foundation statistical methods as well as techniques for producing artificial intelligence.
UNSW Online
Build knowledge and skills in machine learning with the 100% online Master of Data Science at UNSW. Machine learning is an area you concentrate on with subjects that include Principles of Programming; Data Mining and Machine Learning; Neural Networks and Deep Learning; and Bayesian Inference and Computation. The program develops sought-after capabilities for immediate use. Students explore how to organise, identify, analyse and use data to inform strategies and find impactful answers.
Strategy and Leadership
A Strategy and Leadership major is 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 required.
RMIT University
Top companies are looking for data scientists with excellent communication as well as technical skills. Technical competence has limited value if you can't convert that ability into real impact. RMIT's Master of Data Science Strategy and Leadership is about producing high-value graduates with management skills. The 100% online degree consists of 12 seven-week subjects. You can study year-round while working full-time. Topics include practical data science with Python, consumer analytics, machine learning for decision makers, and shaping organisations with artificial intelligence.
Entry Requirements
These are challenging programs that require you to be a good student with strong maths ability. Course prerequisites vary but you're generally expected to have a bachelor degree. Ideally, this is in a cognate discipline such as Computer Science, Economics, Mathematics or Statistics. Data experience may help you gain entry to some programs.
Here are examples of course admission requirements. Enquire for further details.
To be eligible for the online Master of Data Science (Applied), you need a bachelor degree or equivalent in any discipline with a minimum GPA of 4.5 (7.0 GPA scale) and to have passed SACE Stage 2 Mathematical Methods (or equivalent) during Senior Secondary School.
Without SACE Stage 2 Maths Methods or equivalent, you can enrol in the Graduate Certificate in Data Science (Applied) and MathTrackX. MathTrackX covers the maths needed to continue to the master's course.
JCU Online's program is open to students who have a bachelor degree (although not a prerequisite for entry, high numeracy skills that includes algebra and elementary differential calculus is assumed) OR at least five years of relevant work experience in an IT or data-related industry (including some work in computing, data analysis or programming).
English language proficiency requirements apply.
Recognition of Prior Learning (RPL) is available on a case-by-case basis. Recognising the value of previous study and real-world experience, exemptions and credits may be issued after submission of appropriate evidence.
Tuition fees are $3,700 per subject in 2023. FEE-HELP loans are available to cover course costs.
Entry requirements at RMIT Online
16-subject Master of Data Science Strategy & Leadership: An Australian bachelor degree (or equivalent) in any discipline.
12-subject masters: An Australian bachelor degree (or equivalent), or higher-level qualification, in a business or related discipline OR the RMIT Graduate Certificate in Data Science.
Tuition fees
Tuition fees are $3,840 per subject in 2023. FEE-HELP loans are available for eligible Australian students.
To be eligible for the masters, you must have a bachelor degree in a cognate discipline (e.g. Computer Science, Economics, Mathematics, Statistics) AND a sufficient data science background as indicated by an average mark of 70+ across three Level III courses in Mathematics and/or Statistics and/or Computer Science and/or Econometrics.
Alternatively, you can be admitted by having completed the UNSW Graduate Diploma in Data Science course with a WAM of 65 or higher.
Advanced standing in the program is available for cases where core subjects were completed previously.
Key dates: Study intakes occur in January, March, May, July, September and October.
If you have a mainly business background, you may want to consider a Masters in Business Analysis due to the low coding requirements.
For 2023 starters, the indicative fee for the full program is $53,760 for domestic students and $70,740 for international students. FEE-HELP loans to cover tuition fees are available for eligible domestic students.
Data Scientist Careers – Job Ad Snippets
Snippets from jobs ads. Random sample.
Data Scientist – en world
An innovative organisation within the machine learning behavioural analytics marketplace is seeking an experienced professional who wants to stretch themselves beyond just applying theory! The company is a small, motivated, highly intellectual group who have taken the behavioural analytics marketplace by storm! Come and help them drive this forward, very good remuneration and equity on offer.
Spatial data scientist/programmer – CSIRO
The EODS Team develops the data tools, processing techniques and information products for improved management of natural resources through the merging of Earth observations, ground-based measurements and biophysical modelling. We tailor geospatial information products for policy, planning and decision support around managing Australian environmental assets.
IMDA
Conceptualisation through to model deployment in the telco cybersecurity field. Work across the spectrum of data science-related tasks, such as data mining, engineering, statistical analysis, developing machine learning models and evaluating the outputs. Should be familiar with big data streaming tools, database frameworks and visualisation tools such as Apache NiFi, Storm, Spark, Hadoop and Airflow.
Data Scientist (Fraud and Attribution) – Leadbolt
About the Role: Provide performance-based product recommendations including data driven improvements, product features, system optimizations or data usage for Fraud and Attribution products. Data analysis including data modelling, competitor or 3rd party product and market reviews to ensure best in class performance.
Kmart
To help deliver our plans and vision, we've created an Advanced Analytics team. With solid experience in advanced statistics, analytics and machine learning methodologies, coupled with your passion for delivering insights, this is a unique opportunity to impact and shape the discipline from the ground up.
The Iconic
We are looking for an experienced professional to work across several business areas including Recommendations, Customer Profiling, Forecasting and Optimisation. You will be part of a highly innovative team working on interesting and difficult problems, leveraging cutting edge technology to build solutions and customer facing products.
Nearmap
Want to do petabyte scale deep learning and ship product to real customers? We have petabytes of high quality aerial imagery (covering half a million square kilometres a year at 5-7cm resolution). We've also started producing automated 3D models of entire cities.
Horizon Power
Responsibilities include: (i) Develop and promote the use of Data, Data Science, Analytics and Visualisation as a mechanism to increase Horizon Power’s value and support its objectives (ii) Work with stakeholders to understand their data analysis objectives, and assist them to formulate meaningful questions based on available data (iii) Create models that analyse data for insights and predictions.
FAQs
Is a postgraduate degree important for becoming a successful data scientist? The short answer is that the degree could be highly beneficial for your career.
The paths to becoming a data scientist are many since the field combines multiple disciplines. Common bachelor degrees for practitioners are in computer science, business, maths and statistics, data analytics, and engineering. But, still, 75% of data scientists have a master's degree of some kind.
Some people become data scientists mostly via self-training. However, a master's degree helps tie the threads of your previous learning together and fill any large gaps. Programs are increasingly designed to give you the skills that are most in demand by industry employers.
Students learn: (a) how to structure databases and produce clean data for analysis (b) programming skills for accessing and manipulating data (c) computational statistics and descriptive analysis (d) mathematical and statistical modelling and AI and (e) how to connect data analysis to decision making. In acquiring a broad set of data science skills, you prepare yourself for innumerable future roles to do with generating value from information assets.
You can study for a data science masters online with a number of Australian universities. Technology courses are widely available online, including in data analytics and related fields.
Accelerated courses
The most popular version of online data science studies is the accelerated course. This type of program is purpose built for online learning by working professionals. Students do one subject at a time, with each completed from start to finish over a 6-7 week study period.
There are no exams, with assessment done continuously through assignments, reports, quizzes and alike. With a new study period starting every couple of months, you can progress fairly quickly through the part-time program at a rate of 6 subjects per year.
Virtual classes
Online universities almost always provide virtual classes so that your learning experience is similar to on campus. You'll have a weekly schedule, tutorials and assignments, and regular access to instructors and classmates. If you prefer a group environment, which can definitely keep you motivated and on track, that is offered virtually.
Program participants also generally have access to a Student Success Advisor. This person is there to provide help and advice with any non-academic aspects of your remote learning experience.
You can expect a data science masters to essentially be a continuation of your previous STEM studies. Students are expected to have a strong background in mathematics plus familiarity with coding. If you have these qualities, which are often required to gain admission, successful completion of the program is achievable.
Subject difficulty
The program will likely have many technical subjects that rely on your aptitude for logic and problem solving. An exception to this is a strategy and leadership program, which has limited technical content.
The difficulty of individual subjects is similar to bachelor degrees at 2nd and 3rd year levels. Instructors don't ramp up standards just because a course is postgraduate. You may find some subjects quite easy while others could be demanding. If you were a good student in bachelor studies, you should be able to continue achieving solid grades.
Program breadth
You might be concerned about how many different topics you need to learn in a master's degree. But you also need to consider that you'll only be focusing on one subject at a time. By the end of the program, you're not expected to remember every single thing you've learned.
Your exposure to the breadth of topics will make it easier to handle the demands of the profession. Because of their broad university education, graduates are well placed to refresh their knowledge, develop particular strengths, and add or become proficient with certain tools according to the everyday demands of their jobs.
