Key facts
Duration
2 years part-time
Locations
Current Deakin Students
To access your official course details for the year you started your degree, please visit the handbook
Course overview
Modern organisations are placing increasing emphasis on the use of data to inform day-to-day operations and long-term strategic decisions, resulting in high demand for data scientists. This course equips you with the essential skills and knowledge to meet this demand and excel an area of high job growth.
The Graduate Diploma 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. This course gives you essential skills in data analytics, enabling you to discover insights and support decision-making across a range of industries.
Course information
- Award granted
- Graduate Diploma of Data Science
- Year
2024 course information
- Deakin code
- S677
- Level
- Postgraduate (Graduate Certificate and Graduate Diploma)
- 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 8.
Course structure
To complete the Graduate Diploma of Data Analytics, students must attain 8 credit points.
The course is structured in two parts:
- Part A: Fundamental Data Analytics Studies (4 credit points)
- Part B: Core Data Science Studies (4 credit points)
- completion of DAI001 Academic Integrity Module (0-credit point compulsory unit).
Depending upon prior qualifications and/or experience, you may receive credit for Part a.
Core
Mandatory unit for all entry levels
Part A: Fundamental Data Analytics Studies
Plus one level 7 SIT or MIS coded unit#
Part B: Core Data Science Studies
Plus one level 7 SIT or MIS coded unit#
# Excluding SIT771, SIT772, SIT773, SIT774
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.
Trimester 1 - March
- Start date: March
- Available at:
- Online
Trimester 2 - July
- Start date: July
- Available at:
- Online
Trimester 3 - November
- Start date: November
- Available at:
- Online
INTERNATIONAL STUDENTS – Please note that due to Australian Government regulations, student visas to enter Australia cannot be issued to students who enrol in Deakin Online programs.
Additional course information
Course duration
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.
Workload
You can expect to participate in a range of teaching activities each week. This could include lectures, 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.
Participation requirements
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. More information available at Disability support services.
Entry requirements
Admissions criteria
Selection is based on a holistic consideration of your academic merit, work experience, likelihood of success, availability of places, participation requirements, regulatory requirements, and individual circumstances. You will need to meet the minimum course entry requirements to be considered for selection, but this does not guarantee admission.
Academic requirements
To be considered for admission to this degree you will need to meet at least one of the following criteria:
- completion of a bachelor degree or higher in a related discipline
- completion of a bachelor degree or higher in any discipline and at least two years' relevant work experience (or part-time equivalent)
- completion of a Graduate Certificate of Information Technology or equivalent
English language proficiency requirements
To meet the English language proficiency requirements of this course, you will need to demonstrate at least one of the following:
- bachelor degree
- IELTS overall score of 6.5 (with no band score less than 6.0) or equivalent
- other evidence of English language proficiency (learn more about other ways to satisfy the requirements)
Admissions information
Learn more about Deakin courses and how we compare to other universities when it comes to the quality of our teaching and learning.
Not sure if you can get into Deakin postgraduate study? Postgraduate study doesn’t have to be a balancing act; we provide flexible course entry and exit options based on your desired career outcomes and the time you’re able to commit to your study.
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
Fee information
Learn more about fees and your options for paying.
The 'Estimated tuition fee' is provided as a guide only based on a typical enrolment of students completing this course in the same year 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 eight credit points of study. Each unit you enrol in has a credit point value.
The 'Estimated tuition fee' is calculated by adding together eight 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 tuition fees.
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
Applications can be made directly to the University through StudyLink Connect - Deakin University's International Student Application Service. For information on the application process and closing dates, see the How to apply web page.
Fill out the application form and submit to a Deakin International office or take your application form to a Deakin representative for assistance
For information on the application process and closing dates, see the How to apply webpage.
If you’re still having problems, please contact Deakin International for assistance.
Careers
Career outcomes
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 specialised knowledge of data analytics concepts and technologies to solutions based on specifications and user requirements. |
| Communication | 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. |
| Digital literacy | Use digital media to locate, collect and evaluate information from technical channels and apply information to design approaches and solutions that meet user requirements. |
| Critical thinking | Use the frameworks of logical and analytical thinking to evaluate data analytics information, technical problems and user requirements, and develop approaches to identify solutions. |
| Problem solving | Design solutions for automating data analysis processes by investigating technical and business problems; design and propose alternative solutions that improve services and user experiences. |
| Self-management | Demonstrate the ability to work in a professional manner, learn autonomously and responsibly in order to identify and meet development needs. |
| Global citizenship | 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 27 June 2019