To access your official course details for the year you started your degree, please visit the handbook
The Graduate Diploma of Data Analytics provides you with the specialist knowledge required to formulate solutions to complex data problems across a range of business settings – turning raw data sets into meaningful information to better guide business decisions.
This course aims to prepare you for specialised careers in data analytics by providing you with advanced working knowledge in statistics and data science. You’ll draw on previous studies in IT, computing or related disciplines to focus on the specific application of data analysis in a business setting.
You’ll get an understanding of the various origins of data to be used for analysis, combined with the central approaches and methods to manage, organise and manipulate such data, within regulatory, ethical and security constraints. You’ll learn fundamental aspects of data science, modern methods, techniques and applications of data science.
You’ll learn how to identify problems and understand the various techniques and methods that can be used to solve them. You’ll be able to extract meaning from, make sense of, and draw conclusions from data. These skills will enable you to approach and represent different types of data, and to perform data analysis and statistical inference tasks of interest.
Data security and its governance have now become key issues for all organisations. As such, the various ethical, regulatory and governance aspects of analytics systems will be covered. Potential privacy and security issues associated with large data sets and the results obtained from analytics on such data are examined in detail.
As a graduate, you’ll be ready for a career as a software developer, computer systems analyst/architect/engineer, marketing manager, market research analyst and marketing specialist, management analyst, web developer, network and computer systems administrator, IT project manager, or computer or IT research scientist.
Units in the course may include assessment hurdle requirements.Read More
To complete the Graduate Diploma of Data Analytics, students must attain 8 credit points. Most units (think of units as ‘subjects’) are equal to 1 credit point. So that means in order to gain 8 credit points, you’ll need to study 8 units (AKA ‘subjects’) over your entire degree. Most students choose to study 4 units per trimester, and usually undertake two trimesters each year.
The course comprises a total of 8 credit points, which must include the following:
- Completion of STP050 Academic Integrity (0-credit-point compulsory unit)
- Two (2) core analytics units (SIT719, SIT720)
- Four (4) ‘Data’ discipline specific units (SIT741, SIT742, SIT743, SIT744)
- Two (2) level 7 SIT/MIS-coded elective units
Students are required to meet the University's academic progress and conduct requirements. Click here for more information.
Year 1 - Trimester 1
Plus two (2) IT/MIS elective units
Year 1 - Trimester 2
Select the remaining 2 credit points from a range of level 7 SIT/MIS-coded elective units.
Campuses by intake
Campus availability varies per trimester. This means that a course offered in Trimester 1 may not be offered in the same location for Trimester 2 or 3. Read more to learn where this course will be offered throughout the year.
Trimester 1 - March
- Start date: March
- Available at:
- Burwood (Melbourne)
- Cloud Campus
Trimester 2 - July
- Start date: July
- Available at:
- Burwood (Melbourne)
- Cloud Campus
Trimester 3* - November
- Start date: November
- Available at:
- Burwood (Melbourne)
- Cloud Campus
Trimester 3 intake is only offered on a part-time basis.
Additional course information
Course duration - additional information
Course duration may be affected by delays in completing course requirements, such as accessing or completing work placements.
Mandatory student checks
Any unit which contains work integrated learning, a community placement or interaction with the community may require a police check, Working with Children Check or other check.
Elective units may be selected that include compulsory placements, work-based training, community-based learning or collaborative research training arrangements.
Reasonable adjustments to participation and other course requirements will be made for students with a disability. Click here for more information.
Deakin University offers admission to postgraduate courses through a number of Admission categories. In all categories of admission, selection is based primarily on academic merit as indicated by an applicant's previous academic record.
All applicants must meet the minimum English language requirements.
- Bachelor degree in a related discipline.
For more information on the Admission Criteria and Selection (Higher Education Courses) Policy visit the Deakin Policy Library.
Credit for prior learning
The University aims to provide students with as much credit as possible for approved prior study or informal learning which exceeds the normal entrance requirements for the course and is within the constraints of the course regulations. Students are required to complete a minimum of one-third of the course at Deakin University, or four credit points, whichever is the greater. In the case of certificates, including graduate certificates, a minimum of two credit points within the course must be completed at Deakin.
You can also refer to the Credit for Prior Learning System which outlines the credit that may be granted towards a Deakin University degree and how to apply for credit.
Fees and scholarships
Learn more about fees and your options for paying.
The available fee places for this course are detailed above.
Tuition fees are determined by your enrolment:
- If you are offered a full fee paying place, your tuition fees are calculated based on your course.
- If you are offered a Commonwealth supported place, your tuition fees are calculated depending on the units you choose. Not all courses at Deakin have Commonwealth supported places available.
The 'Estimated tuition fee' is provided as a guide only based on a typical enrolment of students completing the first year of this course. The cost will vary depending on the units you choose, your study load, the length of your course and any approved Credit for Prior Learning.
* One year full-time study load is typically represented by eight credit points of study. Each unit you enrol in has a credit point value. The 'Estimated tuition fee' is calculated by adding together 8 credit points of a typical combination of units for your course.
You can find the credit point value of each unit under the Unit Description by searching for the unit in the Handbook.
Learn more about fees and available payment options.
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 $51,956.
Please note: fees shown by the calculator are indicative only and based on 2019 rates. Actual fees may vary. We advise confirming fees with Prospective Student Enquiries prior to enrolment.
Estimate your FEE-HELP repayments
after FEE-HELP and tax
Your estimated FEE-HELP repayments
- $* is the 2019 estimated tuition fee for a Graduate Diploma of Data Analytics (8 credit points) at Deakin
- is the annual FEE-HELP payment, based on your current salary
- of your current salary be spent on FEE-HELP
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 15% Deakin Alumni Postgraduate Course Fee Bursary);
- assumes the maximum number of units that need to be successfully completed actual number completed may be reduced if Credit for 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.
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.
If you’re a Deakin alumni commencing a postgraduate award course, you may be eligible to receive a 15% reduction per unit on your enrolment fees. Your spouse and members of your immediate family may also be eligible to apply for this bursary.
How to apply
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.
Please complete the Register your interest form to receive further information about our direct application opportunities.
Further study options
Frequently asked questions
How do I apply?
We provide step-by-step guidance online to make applying to Deakin easy. And, with three study periods a year, the next intake is never far away. Learn more about the application process and entry requirements by visiting our How to apply page.
When do applications close?
Application deadlines depend on the course and trimester you’re applying for.
Find out the application open and close dates for your course by visiting our Key dates page.
Missed the application cut-off? The good news is Deakin has three study periods a year, which means the next intake is never far away.
How do fees work?
Fees are paid according to the units you study each trimester.
Don’t worry, you don’t need to pay your course fees upfront. There are different loans available depending on the type of student you are and the course you’re applying for.
For more information on fees, including payment assistance, and understanding what type of student you are, visit our Fees hub.
If we haven’t answered your question, our student enquiries team is ready to help.
Why choose Deakin
Graduates of this course may find careers as software developers, computer systems analysts/architects/engineers, marketing managers, market research analysts and marketing specialists, management analysts, web developers, network and computer systems administrators, IT project managers, computer and IT research scientists.
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
Course Learning Outcomes
Discipline-specific knowledge and capabilities
Develop specialised knowledge of data analytics concepts and technologies to solutions based on specifications and user requirements.
Communicate data analytical solutions as appropriate to the context to inform, motivate and effect change utilising a range of verbal, graphical and written methods, recognising the needs of diverse audiences.
Use digital media to locate, collect and evaluate information from technical channels and apply information to design approaches and solutions that meet user requirements.
Use the frameworks of logical and analytical thinking to evaluate data analytics information, technical problems and user requirements, and develop approaches to identify solutions.
Design solutions for automating data analysis processes by investigating technical and business problems; design and propose alternative solutions that improve services and user experiences.
Demonstrate the ability to work in a professional manner, learn autonomously and responsibly in order to identify and meet development needs.
Engage in professional and ethical behaviour in the design of data analytics systems, in a global context, in collaboration with diverse communities and cultures.
Approved by Faculty Board 7 June 2018