Master On Campus

Data Science

RMIT University

24 months
37440 AUD/year
30720 AUD/year
Tuition fee
Apply date
Start date


Harness the power of big data and become a data scientist with this Master of Data Science from RMIT University.  

Visit the official programme website for more information


Data science has been called the “sexiest job of the 21st century”, and those who can manage and make sense of big data will undoubtedly take on some of the most important roles in the information age. 

We live in a data-driven world that’s generating huge volumes of information at ever-increasing rates via social media, financial transactions, transportation, and even scientific discovery. As a consequence, an understanding of data is a top priority for all of us – whether you’re in business, industry and government, or individually as citizens and consumers. 

The new interdisciplinary field of data science combines areas of computer science with mathematical statistics and domain expertise to manage and analyse data. Specialists develop the capability to derive insight and opportunity from the vast repositories of information that organisations collect. Data science also puts a greater emphasis on the specialised computational skills required to manage and analyse big data from sources such as social media, massive sensors, mobile and transaction data. It enables businesses to gain a competitive edge, governments to deliver more targeted services, and research teams make new discoveries.

Data science and its analysis could appeal to people from a broad range of backgrounds, such as graduates from computing, mathematics, science, engineering or health.

Through this Master of Data Science from RMIT University , you'll build mix of skills in analytics, statistics and computer science that will enable you to be central to business decision-making, corporate strategy and government planning. This prepares graduates for a career in a field that is driving scientific research, economic growth, public policy and corporate strategy, using cloud technologies to aid the management and analysis of very big data sets.

This course also provides opportunities to experience an industry project where you’ll undertake a capstone project giving you hands-on, practical experience analysing data in a business setting. Working within a corporate environment, you’ll integrate the knowledge you’ve acquired throughout the course into a solid skills base to take into your professional life.

Exposure to theoretical knowledge and practical expertise means that graduates of the Master of Data Science have the potential to become influential leaders within their organisations.


Any organisation handling large volumes of data needs qualified data scientists. Organisations in all sectors of the economy – IT, business, banking and finance, science and engineering, government, health and medical – can gain a competitive edge by better managing and analysing their data.

As data science is still a new and emerging field, the roles available are consequently quite varied and diverse.

As well as the title of Data Scientist, other positions include analytics specialist, business intelligence analyst/developer, data analyst, data architect, data engineer, data miner, research scientist and web analyst.

While industry expertise is at the heart of program delivery, studying at RMIT also means you are physically located close to Melbourne’s data professionals in the central business district, with many opportunities for developing links to local industry and jobs, including meet-ups, events and seminars, as well as other networking occasions.

After being exposed to the latest theoretical and practical expertise, graduates are expected to become influential leaders within their organisations.

There is also a research stream in this course, in which students work with a data science researcher on more technical data science innovation.

Programme Structure

Courses include:

  • Practical Data Science with Python
  • Programming Fundamentals
  • Database Concepts
  • Applied Analytics  
  • Data Wrangling
  • Advanced Programming

Key information


  • Full-time
    • 24 months
  • Part-time
    • 48 months

Start dates & application deadlines

More details



On Campus

Academic requirements

GPA admission requirements GPA

Other requirements

General requirements

  • An Australian bachelor degree in computing, science, engineering, health, or statistics with a GPA of at least 2.0 out of 4. 0, or equivalent. 
  • You may also be considered if you have an Australian bachelor degree with a GPA of at least 2.0 out of 4.0, or equivalent and; relevant completed courses in programming and statistics in an undergraduate or postgraduate degree or a minimum three years’ of current, relevant work experience or professional practice as a programmer, statistician or equivalent.
  • CRICOS number: 093313B  

Tuition Fee

To alway see correct tuition fees
  • International

    37440 AUD/year
    Tuition Fee
    Based on the tuition of 37440 AUD per year during 24 months.
  • National

    30720 AUD/year
    Tuition Fee
    Based on the tuition of 30720 AUD per year during 24 months.

Living costs for Melbourne

1501 - 2659 AUD /month
Living costs

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.



Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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