Key facts

Duration

1 year full-time

Locations

Online

Course overview

Modern organisations are increasingly emphasising the use of data to inform both daily 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 in a high-job growth area.

The Graduate Diploma of Data Science introduces you to modern data science concepts, statistical analysis, descriptive analytics and machine learning. You will gain the theory, methodologies, techniques and tools needed to confidently work with all types of data – identifying trends, making predictions, driving innovation and influencing decisions. With these in-demand skills, you will be ready to deliver valuable insights and support evidence-based decision-making across a wide range of industries.

Current Deakin students

To access your official course details for the year you started your degree, please visit the handbook

Award granted
Graduate Diploma of Data Science
Year

2026 course information

Deakin code
S677
Level
Postgraduate (Graduate Certificate and Graduate Diploma)
Australian Qualifications Framework (AQF) recognition

The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 8

Flexible course delivery

Deakin’s blend of online and on-campus learning means you can balance work, study and personal development. Achieve work-life balance – study with Deakin's dedicated support and flexible learning options.

Course structure

To complete the Graduate Diploma of Data Science students must pass 8 credit points. The number of credit points required may vary, depending on your entry point or how much credit you receive as recognition of prior learning (RPL) based on your professional experience and previous qualifications.

An 8-credit point Graduate Diploma of Data Science includes:

Most units are equal to one credit point. As a full-time student you will study four credit points per trimester and usually undertake two trimesters per year.

All students are required to meet the University's academic progress and conduct requirements.

4
Fundamental data analytics units
+
4
Core data science units
=
8
Total
Academic Integrity and Respect at Deakin (0 credit points)
Real World Analytics
Data Wrangling
Mathematics for Artificial Intelligence
Machine Learning

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.

  • Start date: March
  • Available at:
    • Online

    *Full time or part-time available

  • Start date: July
  • Available at:
    • Online

    *Full time or part-time available

  • Start date: November
  • Available at:
    • Online

    *Only part-time available

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.

Equipment requirements

The learning experiences and assessment activities within this course may require students to have access to a range of technologies beyond a laptop or desktop computer. For information regarding hardware and software requirements, please refer to the Bring your own device (BYOD) guidelines via the School of Information Technology website in addition to the individual unit outlines in the Handbook.

Course duration

You may be able to study available units in the optional third trimester to fast-track your degree, however your course duration may be extended if there are delays in meeting course requirements, such as completing a placement.

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

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 academic and English language proficiency requirements or higher to be considered for selection, but this does not guarantee admission.

A combination of qualifications and experience may be deemed equivalent to minimum 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).

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 are 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 (RPL) 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

Estimated tuition fee - full-fee paying place

$44,200 for 1 yr full-time AUD
Learn more about fees and your options for paying.

The tuition fees you pay are determined by the course you are enrolled in. The 'Estimated tuition fee' is provided as a guide only and represents the typical tuition fees for students completing this course within 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 fees and available payment options.

Scholarship options

Deakin scholarships recognise your hard work and achievements. Our support can ease the financial pressure of studying in Australia so you stay focused on your success. Numbers are limited, so apply early for the best chance.

Find a scholarship that can support you

Postgraduate bursary

We love welcoming Deakin alumni back to continue their journey with us. If you're starting a postgraduate award course, you may be eligible for a 10% discount on your enrolment fees, applied per unit. It's our way of supporting your next step.

Learn more about the 10% Deakin alumni discount

Apply now

Apply directly to Deakin

Applications can be made directly to the University through StudyLink Connect - Deakin University's International Student Application Service.

We recommend engaging with a Deakin Authorised Agent who can assist you with the process and submit the application.

APPLY THROUGH STUDYLINK CONNECT

Need more information on how to apply?

For information on the application process, including required documents and important dates, see the How to apply webpage.
If you need assistance, please contact us.

Pathways

Upon completion of the Graduate Diploma of Data Science, you could use the credit points you’ve earned to enter into further study, including:

Alternate exits

Career outcomes

Graduates of this course are prepared for professional employment across all sectors as data science specialists. Professionals with solid knowledge in data science and strong skills for analysing and interpreting data are in high demand in today's data-rich economy. You may find a career as a data analyst, data scientist, analytics programmer, analytics manager, analytics consultant, business analyst, management adviser, management analyst, business adviser and strategist, marketing manager, market research analyst and marketing specialist.

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 in a professional context to inform, explain and drive sustainable innovation through data science and to motivate and effect change, utilising a range of verbal, graphical and written methods, recognising the needs of diverse audiences.

Digital literacy

Identify, select and use digital technologies, platforms, frameworks, and tools from the field of data science to generate, manage, process and share digital resources.

Critical thinking

Evaluate and critically analyse information provided and their sources to inform decision making and evaluation of plans and solutions associated with the field of data science.

Problem solving

Apply advanced cognitive, technical, and creative skills from data science to understand requirements and design, implement, operate, and evaluate solutions to real-world and ill-defined computing problems.

Self-management

Work independently to apply knowledge and skills in a professional manner to new situations and/or further learning in the field of data science with adaptability, autonomy, responsibility, and personal accountability for actions as a practitioner and a learner.

Global citizenship

Apply professional and ethical standards and accountability in the field of data science, and openly and respectfully collaborate with diverse communities and cultures.

*Deakin references data from a range of government, higher education and reputable media sources. For more information, visit our University rankings page.

Discover more