Key facts
Locations
Key dates
Direct applications to Deakin for Trimester 2 2024 close 23 June 2024
Direct applications to Deakin for Trimester 3 2024 close 27 October 2024
Current Deakin Students
To access your official course details for the year you started your degree, please visit the handbook
Course overview
Deakin’s Master of Data Analytics prepares students for professional employment across all sectors. The sheer volume and complexity of data already at the fingertips of businesses and research organisations gives rise to challenges that must be solved by tomorrow’s graduates. Become a data analytics specialist capable of using data to learn insights and support decision making.
Modern organisations are placing increasing emphasis on the use of data to inform day-to-day operations and long-term strategic decisions.
Throughout your studies you’ll learn to understand the various origins of data to be used for analysis, combined with methods to manage, organise and manipulate data within regulatory, ethical and security constraints. You’ll develop specialised skills in categorising and transferring raw data into meaningful information for the benefit of prediction and robust decision-making.
As a graduate, your knowledge, skills and competencies in modern data science and statistical analysis will be highly valued by employers seeking greater efficiencies and competitive advantage through data insights.
Units in the course may include assessment hurdle requirements.
Read MoreCourse information
- Award granted
- Master of Data Analytics
- Year
2017 course information
- Deakin code
- S777
- CRICOS code?
- 089186E
- Approval status
- This course is approved by the University under the Higher Education Standards Framework.
- Australian Qualifications Framework (AQF) recognition
The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 9.
Core
Year 1 - Trimester 1
Year 1 - Trimester 2
Year 2 - Trimester 1
plus two course grouped elective units
Year 2 - Trimester 2
plus two course grouped elective units
Electives
Four (4) level 7 SIT/MIS course grouped elective units, which may include the following:
Intakes by location
The availability of a course varies across locations and intakes. This means that a course offered in Trimester 1 may not be offered in the same location for Trimester 2 or 3. Check each intake for up-to-date information on when and where you can commence your studies.
Workload
You can expect to participate in a range of teaching activities each week. This could include classes, seminars, practicals and online interaction. You can refer to the individual unit details in the course structure for more information. You will also need to study and complete assessment tasks in your own time.
Work experience
You will have an opportunity to undertake a discipline-specific internship placement as part of your course. deakin.edu.au/sebe/wil.
Entry requirements
FEE-HELP calculator
What is FEE-HELP?
FEE-HELP loans cover up to 100% of tuition fees for eligible students. By taking out a FEE-HELP loan, the government pays your tuition fees directly to Deakin, and the balance is repaid from your employment income - but only once you're earning over $51,550.
Please note: fees shown by the calculator are indicative only and based on 2024 rates. Actual fees may vary. We advise confirming fees with Prospective Student Enquiries prior to enrolment.
Estimate your FEE-HELP
FEE-HELP payments
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after FEE-HELP and tax
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Your estimated FEE-HELP repayments
- $* is the estimated full cost for a Master of Data Science (16 credit points), based on the 2024 fees.
- is the annual FEE-HELP payment, based on your current salary
- of your current salary be spent on FEE-HELP
*Disclaimer
Deakin University (Deakin):
- gives no warranty and accepts no responsibility for the currency, accuracy or the completeness of the information provided;
- advises users that no reliance should be placed upon on the information provided, and;
- instructs users that they should confirm the actual course fee with Prospective Student Enquiries prior to enrolment.
This tool provides indicative information about the fees that will be payable in respect of courses and subjects offered to prospective students domiciled in Australia during the periods indicated.
Please note that the fees shown by the calculator are indicative only and actual fees may vary. Users are advised to confirm the actual course fee with Prospective Student Enquiries prior to enrolment.
The estimated course fee is based on the tuition fee costs applicable to a domestic full time student commencing the course in Trimester 1 and studying full time for the duration of the course but:
- does not include non-tuition costs that may apply, such as Student Services and Amenities Fees (SSAF);
- does not take into account any scholarships or bursaries awarded to the student (including the 10% Deakin alumni discount);
- assumes the maximum number of units that need to be successfully completed actual number completed may be reduced if recognition of prior learning is granted;
- assumes that no exceptional, or non-typical, circumstances apply to the proposed course of study;
- assumes that the options that the user selects are appropriate for the course of study that they intend to undertake;
- where fees are estimated for future years those fee will be subject to annual increases in accordance with increases in the cost of course delivery.
Scholarship options
A Deakin scholarship might change your life. If you've got something special to offer Deakin – or you just need the financial help to get you here – we may have a scholarship opportunity for you.
Postgraduate bursary
If you’re a Deakin alumnus commencing a postgraduate award course, you may be eligible to receive a 10% reduction per unit on your enrolment fees.
Apply now
Some of our courses have limited places available - for the latest on courses still open for application, visit Courses by trimester.
Create an account in the Deakin Application Portal, start your application, enter personal details, education experience, upload supporting documents and submit. Need help? Play this video, or contact one of our friendly future student advisers on 1800 693 888 or submit an online enquiry.
For more information on the application process and closing dates, see the How to apply webpage. If you're still having problems, please contact us for assistance.
Entry pathways
Alternative exits
- Graduate Certificate of Data Analytics (S576)
- Graduate Diploma of Data Science (S677)
Contact information
Faculty of Science, Engineering and Built Environment
School of Information Technology
Tel 03 9244 6699
sebe@deakin.edu.au
www.deakin.edu.au/information-technology
Course learning outcomes
Deakin's graduate learning outcomes describe the knowledge and capabilities graduates can demonstrate at the completion of their course. These outcomes mean that regardless of the Deakin course you undertake, you can rest assured your degree will teach you the skills and professional attributes that employers value. They'll set you up to learn and work effectively in the future.
Deakin Graduate Learning Outcomes (DGLOs) | Course Learning Outcomes (CLOs) |
1. Discipline-specific knowledge and capabilities: appropriate to the level of study related to a discipline or profession. |
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2. Communication: using oral, written and interpersonal communication to inform, motivate and effect change. |
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3. Digital literacy: using technologies to find, use and disseminate information. |
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4. Critical thinking: evaluating information using critical and analytical thinking and judgment. |
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5. Problem solving: creating solutions to authentic |
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6. Self-management: working and learning independently, and taking responsibility for personal actions. |
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7. Teamwork: working and learning with others from different disciplines and backgrounds. |
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8. Global citizenship: engaging ethically and productively in the professional context and with diverse communities and cultures in a global context. |
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Approved by Faculty Board 14 July 2016
Events Explore more events
We invite industry speakers to our classrooms to show our students what they can do with the knowledge of data analysis and optimisation in real-life.
Vicky Mak
Senior lecturer, School of Information Technology