Progressive, real-world learning. Online.
One year part-time
Direct applications to Deakin for Trimester 2 2021 have closed
Current Deakin Students
To access your official course details for the year you started your degree, please visit the handbook
The Graduate Certificate of Data Science covers modern data science concepts, statistical data analysis, descriptive analytics and machine learning to equip you with the theory, methodologies, techniques and tools of modern data science. Through this course, you will develop the ability to confidently work with any type of data, to identify trends, make predictions, draw conclusions, drive innovations, make decisions and share information that influences people.
The sheer volume and complexity of data already available to businesses gives rise to challenges that must be solved by tomorrow’s graduates. Employers are placing increasing emphasis on the use of data to inform day-to-day operations and long-term strategic decisions. This course gives you essential skills in data analytics, enabling you to discover insights and support decision-making across a range of industries.
To complete the Graduate Certificate of Data Science, students must attain 4 credit points, which must include the following:
- Four (4) core Introductory Data Science Studies units (SIT720, SIT741, SIT742, MIS771) (4 credit points)
- Completion of STP050 Academic Integrity (0-credit point compulsory unit)
Students are required to meet the University's academic progress and conduct requirements. Click here for more information.
Year 1 - Trimester 1
Year 1 - Trimester 2
2022 course information
This course is approved by the University under the Higher Education Standards Framework.
The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 8.
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
INTERNATIONAL STUDENTS – Please note that due to Australian Government regulations, student visas to enter Australia cannot be issued to students who enrol in Deakin’s Cloud Campus.
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.
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.
Reasonable adjustments to participation and other course requirements will be made for students with a disability. Click here for more information.
Entry will be based on performance in:
- Bachelor's degree (AQF7) in a related discipline; OR
- 2 years relevant work experience; OR
- Graduate Certificate of Data Analytics (or equivalent); OR
- Evidence of academic capability judged to be equivalent.
Deakin University offers admission to postgraduate courses through a number of Admission categories.
All applicants must meet the minimum English language requirements.
Please note that meeting the minimum admission requirements does not guarantee selection, which is based on merit, likelihood of success and availability of places in the course.
For more information on the Admission Criteria and Selection (Higher Education Courses) Policy visit the Deakin Policy Library
Recognition of 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 Recognition of 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. 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 this course within the same year as they started. The cost will vary depending on the units you choose, your study load, the length of your course and any approved Recognition of Prior Learning.
One year full-time study load is typically represented by four credit points of study for Graduate Certificates. Each unit you enrol in has a credit point value. The 'Estimated tuition fee' is calculated by adding together four 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 $46,620.
Please note: fees shown by the calculator are indicative only and based on 2021 rates. Actual fees may vary. We advise confirming fees with Prospective Student Enquiries prior to enrolment.
Estimate your FEE-HELP
per pay cycle
after FEE-HELP and tax
per pay cycle
Your estimated FEE-HELP repayments
- $* is the estimated full cost for a Graduate Certificate of Data Science (4 credit points), based on the 2021 fees.
- 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 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.
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 alumnus commencing a postgraduate award course, you may be eligible to receive a 10% reduction per unit on your enrolment fees.
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.
Further study options:
Upon completion of the Graduate Certificate of Data Science, you could use the credit points you’ve earned to enter into further study, including:
S777 Master of Data Science
Faculty of Science, Engineering and Built Environment
School of Information Technology
Prospective student enquiries
Are you looking to apply for this course or would like further information?
Call 1800 693 888 or email us at email@example.com
Current student course and enrolment enquiries
Call 03 9244 6699 or email us at firstname.lastname@example.org
Submit an online enquiry
Graduates of this course are prepared for professional employment across all sectors as data science specialists. Professionals with a solid knowledge in data science and strong skills for analysing and interpreting data in today's data-rich economy are in high demand and may find careers as data analysts, data scientists, analytics programmers, analytics managers, analytics consultants, business analysts, management advisors, management analysts, business advisors and strategists, marketing managers, market research analysts and marketing specialists.
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 data analytics solutions based on user requirements by applying coherent knowledge of the analytics discipline using various machine learning and big data analytics tools and techniques. Apply statistical analysis and visualisation techniques appropriately to interpret analytics outcomes.
Communicate effectively in order to design, evaluate and respond to a range of data analytics problems and utilise a range of verbal, graphical and written forms, customised for diverse audiences.
Utilise a range of digital technologies and information sources to discover, select, analyse, evaluate and disseminate both technical and professional information.
Appraise information using logical and analytical thinking to identify user requirements and propose appropriate solutions.
Design solutions for automating data analysis processes by applying foundational technical knowledge and tools.
Work autonomously and responsibly to create solutions to user problems and actively apply fundamental knowledge of data science and methodologies to meet user requirements.
Work independently and collaboratively towards achieving the outcomes of a group project.
Engage in professional and ethical behaviour in the collection, processing, and presentation of data.
Approved by Faculty Board 6 September 2018