Master of Data Science
Student type:
Quick facts
-
Entry score
Not applicable
-
Duration
Part-time 4 years, Full-time 2 years -
Location
Melbourne City -
Fees
AU$27,840 (2019 annual)
Next intake
February, July Entry score
6.5 IELTS
Duration
Full-time 2 years Location
Melbourne City
Overview
Harness the power of big data with the Master of Data Science. With a mix of analytics and computer science you’ll be central to business decision-making, corporate strategy and government planning.
We live in a data-driven world that’s generating huge volumes of information at ever increasing rates, via social media, financial transactions, telecommunications, and even scientific discovery.
Handling this big data is consequently a top priority for all of us, whether you’re in business, industry, government, or even individually, as citizens and consumers.
The emerging interdisciplinary field of data science combines areas of computer science with mathematical statistics and domain expertise to manage and analyse this data.
Though incorporating statistical methods, data science puts a greater emphasis on the specialised computational skills required to manage and analyse big data from sources such as social media, sensors, mobile and transaction data.
Data scientists develop the capability to derive insight and opportunity from the vast repositories of data that many organisations collect.
They help organisations in all sectors of the economy to make sense of these very large volumes of data; enabling businesses to gain a competitive edge, governments to deliver more targeted services, and research teams make new discoveries.
Data science and the analysis of big data could appeal to people from a whole range of backgrounds, such as graduates from computing, mathematics, science, engineering or health.
Despite sharing a number of courses with the Master of Analytics, the Master of Data Science has a significant core of both computer science and statistics.
This prepares graduates for a career working 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.
There are opportunities to experience an industry internship, and you will also undertake a capstone project that gives you hands-on, practical experience analysing data in a project setting.
The emphasis is on working within a corporate environment and integrating all the knowledge you’ve acquired throughout the program into a solid skills base to take into your professional life.
After being exposed to the latest theoretical and practical expertise, graduates of the Master of Data Science are expected to become influential leaders within their organisations.
It’s been called the “sexiest job of the 21st century”, but whether or not that’s true, data scientists that can manage and make sense of big data are among the most important roles in the information age.
Details
RMIT is committed to providing students with an education that strongly links formal learning with workplace experience.
You will learn through a broad mix of study modes including lectures, tutorials, practical classes, project work and seminars using face-to-face, online and other flexible delivery mechanisms.
The program has substantial links with the data science profession and related areas of industry, both within Australia and internationally.
The courses are taught by academics with strong research backgrounds and links to industry, as well as sessional teachers and guest lecturers currently working in industry.
Employers and industry professionals with data science expertise are members of our Industry Advisory Committee and have contributed to the initial development and ongoing improvement of the program.
Their involvement ensures that the program remains relevant to your needs as a graduate and the needs of graduate employers.
Academics teaching in the program are also involved with RMIT Data Analytics Lab, which is a hub for advanced data analytics projects, supporting researchers and helping Australian and Victorian businesses compete on a global scale.
Originally launched as a joint initiative between RMIT University and National ICT Australia (NICTA) - now Data61 - the lab applies text, user and data analytics research to industry-driven projects that solve problems and provide efficiencies in key areas including health, logistics, smart cities, environment and security.
With its industry links and data focus, the lab is an excellent resource for master students to gain networking access to researchers in the field and project partners.
In addition, local ‘meet-ups’ provide clear pathways into the data science community on both a social and professional level.
Those involved in teaching the program, whether from industry or academia, attend these meet-ups and expect that their students will join those that follow their interests too.
- 1.5 years full-time or 3 years part-time (with advanced standing)
- 2 years full-time or 4 years part-time (without advanced standing)
- 1 year full-time or 2 years part-time, Graduate Diploma of Data Science available as exit award.
- 1.5 years full-time or 3 years part-time (with advanced standing)
- 2 years full-time or 4 years part-time (without advanced standing)
- 1 year full-time or 2 years part-time, Graduate Diploma of Data Science available as exit award.
International student visa holders can only study full-time.
The first year of the program develops a solid foundation in computer science and statistics - core skills necessary for every data scientist in their professional work.
Students with an undergraduate background in either of these areas may gain some advanced standing, whereas students from other disciplines will first complete the introductory courses needed to prepare them for studying the advanced core courses and electives in the second year.
The second year also includes a major project, which can be working on an industry or research project while based on campus, or off campus as an internship working as a data scientist in industry.
The real-world focus of this program provides an excellent networking environment that can lead to internship and industry-led project opportunities.
Building a familiarity with statistical techniques and tools, you’ll develop the technical and analytical skills essential to managing large data sets and making sense of them.
Faced with complex collections of data you’ll be able to solve problems through in-depth analysis and evaluation.
Data scientists are often dealing with highly sensitive personal data, so it is imperative that before working on industry projects (for example, as an intern) students undertake case studies with input from industry-based data scientists, looking at the legal, ethical and policy issues in data science.
Choose a program structure
| Title | Location | Duration | Plan code | CRICOS | ||
|---|---|---|---|---|---|---|
| Master of Data Science | City Campus |
2 years full-time
4 years part-time
|
2 years full-time
|
MC267 | 093313B |
Choose a program structure
Program code: MC267
Career
Any organisation handling large volumes of data needs qualified data scientists.
Organisations in all sectors of the economy - IT sector, business sector, science and engineering, government, 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 for data scientists 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.
RMIT is situated in Melbourne’s central business district, with the adjacent biomedical and knowledge precinct to the north - both areas being particular hubs for data science employment.
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, 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 of the Master of Data Science are expected to become influential leaders within their organisations.
Admissions
You must have:
- 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.
OR
- You may also be considered if you have a minimum three years’ of current, relevant work experience or professional practice as a programmer, statistician or equivalent.
International qualifications are assessed for comparability to Australian qualifications according to the Australian Qualifications Framework (AQF).
You must have:
- 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.
OR
- You may also be considered if you have a minimum three years’ of current, relevant work experience or professional practice as a programmer, statistician or equivalent.
International qualifications are assessed for comparability to Australian qualifications according to the Australian Qualifications Framework (AQF).
Entry requirements
To study this program you will need to complete one of the following English proficiency tests:
- IELTS (Academic): minimum overall band of 6.5 (with no individual band below 6.0)
- TOEFL (Paper Based Test): minimum score of 580 (TWE 4.5)
- TOEFL (Internet Based Test - IBT): minimum overall score of 92 (with minimum of 20 in all sections)
- Pearson Test of English (Academic) (PTE (A)): minimum score of 58 (with no communication band less than 50)
- Cambridge English: Advanced (CAE): minimum of 176 with no less than 169 in any component
For detailed information on English language requirements and other proficiency tests recognised by RMIT, visit English language requirements and equivalency information.
Don't meet the English language test scores? Complete an Advanced Plus Certificate at RMIT English Worldwide.
Pathways
Exemptions
Students with relevant studies in computer science, information technology, software engineering, data science, analytics or statistics will be eligible for exemptions as follows:
Qualification level |
Exemptions |
Remaining program duration |
(AQF Level 7 or equivalent)
|
Up to 48 credit points (equivalent to one semester of full-time study) depending on the courses previously studied |
Minimum of 144 credit points (equivalent to three semesters of full-time study) |
(AQF Level 8 or higher)
|
Up to 96 credit points (equivalent to two semesters of full-time study) depending on the courses previously studied |
Minimum of 96 credit points (equivalent to two semesters of full-time study)
|
Fees
2019 indicative fees
Full-fee places: AU$27,840*
* Amount quoted is the indicative 2019 tuition fee per annum, and is based on a standard year of full-time study (96 credit points). A proportionate fee applies for more or less than the full-time study load.
Additional expenses
Student services and amenities fee (SSAF): AU$303 maximum fee for 2019.
Other items related to your program, including field trips, textbooks and equipment.
This program is offered on a full-fee paying basis only. If you are offered a place, you will need to pay the full tuition costs of your program. However, eligible students (such as Australian citizens or holders of an Australian permanent humanitarian visa) may apply to defer payment of some or all of their tuition fees via the Commonwealth Government’s FEE-HELP loan scheme.
Fees shown above apply to 2019 only and are based on an annual full-time study load of 96 credit points unless otherwise noted. A proportionate fee applies for more or less than the full-time study load. Tuition fees are adjusted on an annual basis and these fees should only be used as a guide.
For more information and to learn how to calculate your exact tuition fees see postgraduate study fees.
How does a HELP loan work?
If your FEE-HELP and/or SA-HELP loan application is successful, the Australian Government will pay RMIT, on your behalf, up to 100% of your fees. This amount will become part of your accumulated HELP debt.
You only start repaying your accumulated HELP debt to the Australian Government once you earn above the minimum income threshold for repayment, which is set each year by the Australian Government (this also applies if you are still studying). The Australian Taxation Office (ATO) will calculate your compulsory repayment for the year and include this on your income tax notice.
For more information about loan repayment options see Commonwealth assistance (HELP loans) or Study Assist.
In addition to tuition fees, you will be charged an annual student services and amenities fee (SSAF), which is used to maintain and enhance services and amenities that improve your experience as an RMIT student. The SSAF is calculated based on your enrolment load and the maximum fee for 2019 is $303.
You may be eligible to apply to defer payment of the SSAF through the SA-HELP loan scheme. If you use SA-HELP, the amount will be added to your accumulated HELP debt.
For more information about calculating your actual SSAF see Paying SSAF.
You may also be required to purchase other items related to your program, including field trips, textbooks and equipment. These additional fees and expenses vary from program to program.
The annual tuition fee for 2019 is AU$33,600.
The total indicative tuition fee for 2019 commencement is AU$69,120.
In addition to tuition fees you also need to pay for:
- Student services and amenities fee (SSAF) in each calendar year.
- Overseas Student Health Cover (OSHC) - Student visa holders must have cover for the total duration of their visa.
- Some programs incur additional expenses.
You also need to account for your living expenses. Estimate the cost of living in Melbourne.