Key facts
Duration
2 years full-time or part-time equivalent
Locations
Course overview
The volume and complexity of data available to organisations continues to grow, creating demand for professionals who can analyse, interpret and apply data effectively. Deakin’s Master of Data Science (Professional) equips you with specialised skills in data science, artificial intelligence and machine learning, helping you transform raw data into meaningful insights for prediction and decision-making.
You will develop technical expertise in data modelling, programming, and software development while working with complex datasets from a range of sources to address challenges across industry and government. You will also build an understanding of the ethical, regulatory and security frameworks that guide professional data practice.
In your final year, you can tailor your studies through a professional pathway, with the option to complete a team-based project, industry placement, or research project aligned to your interests and career goals.
Key dates
Direct applications to Deakin for Trimester 3 2026 close 18 October 2026
Direct applications to Deakin for Trimester 1 2027 close 7 February 2027
Current Deakin students
To access your official course details for the year you started your degree, please visit the handbook
- Award granted
- Master of Data Science (Professional)
- Year
2027 course information
- Deakin code
- S770
- CRICOS code?Commonwealth Register of Institutions and Courses for Overseas Students
- 107030E Burwood (Melbourne)
- Level
- Higher Degree Coursework (Masters and Doctorates)
- Australian Qualifications Framework (AQF) recognition
The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 9
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
The Master of Data Science (Professional) is structured in four parts:
- Part A: Fundamental Data Analytics Studies (4 credit points)
- Part B: Mastery Data Science Studies (4 credit points)
- Part C: Specialisation or course electives (4 credit points)
- Part D: Professional Studies (4 credit points)
To complete the Master of Data Science (Professional) you must pass 16 credit points. This includes:
- DAI001 Academic Integrity and Respect at Deakin (0-credit-point compulsory unit) in your first study period
- 8 credit points of core units
- 4 credit points which may comprise of:
- 4 credit point specialisation or
- 4 credit points of course elective units (level 7 SIT or MIS-coded units excluding SIT771, SIT772, SIT773 and SIT774)
- 4 credit points of professional studies capstone units which may comprise of:
- Team Project or
- Professional Practice (subject to meeting unit requirements) or
- Research Project (subject to meeting unit requirements)
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.
Students are required to meet the University's academic progress and conduct requirements.
You are required to complete four core units within Part A (these are essential units for this degree).
In your first trimester you must also complete a 0-credit point unit which are compulsory for all Deakin University degrees.
You have the option to complete a specialisation (four credit points) from the list or four credit points of course elective units (level 7 SIT or MIS-coded units excluding SIT771, SIT772, SIT773 and SIT774).
Refer to the details of each specialisation for availability.
You must choose from one of these Professional Studies options.
Team Project
1 level 7 SIT or MIS-coded elective (1 credit point)~
OR
Professional Practice
OR
Research Project^
Plus 1 unit (2 credit points) from the following:
*Students undertaking this unit must have successfully completed STP710 Career Tools for Employability (0-credit point unit)
~ excluding SIT771, SIT772, SIT773 and SIT774
+ Entry is subject to specific unit entry requirements.
^Students interested in pursuing a Higher Degree by Research (HDR), including a Masters by Research or PhD are encouraged to undertake the Professional Studies – Research Project pathway. High achieving students with a particular interest in research should also consider undertaking either the Research Training in Information Technology specialisation or additional research units as electives (e.g. SIT724, SIT746 and/or SIT747). Students are encouraged to contact Student Central and speak to a course adviser if they are interested in pursuing this option.
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:
- Burwood (Melbourne)
- Online
- Start date: July
- Available at:
- Burwood (Melbourne)
- Online
- Start date: November
- Available at:
- Burwood (Melbourne)
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 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.
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.
Work experience
You may have an opportunity to undertake a placement as part of your course. For more information, please visit deakin.edu.au/sebe/wil.
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)
Examples of related disciplines include, but not limited to the broad field of Information Technology.
To meet the English language proficiency requirements of this course, you will need to demonstrate at least one of the following:
- bachelor degree from a recognised English-speaking country
- 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)
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.
Students intending to gain professional membership of the Australian Computer Society (ACS) on the basis of their study of this program must complete the following units at Deakin University, or equivalent units undertaken within another ACS-accredited program: SIT731, SIT743, SIT744, SIT753, SIT764, SIT782, SIT723, SIT792, SIT791, SIT709.
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.
Recognition of prior learning may be granted for relevant postgraduate studies, in accordance with standard University procedures.
Fees and scholarships
Fee information
Estimated tuition fee - full-fee paying place
$35,000 for 1 yr full-time - Full-fee paying place
Learn more about fees and your options for paying.
Estimated tuition fee - (CSP) ?Enrolling in a Commonwealth Supported Place (CSP) means the Australian Government pays part of your course fees directly to Deakin, and you pay a 'student contribution'.
$9,259 for 1 yr full-time - Commonwealth Supported Place (CSP)
Learn more about fees.
The estimated tuition (student contribution) fee above is based on a typical first-year full-time enrolment of 8 credit points and is provided as a guide only. Your student contribution is determined by the units you enrol in and will vary depending on the units you choose, your study load, the course duration, and any approved recognition of prior learning. You may also be eligible for a HECS-HELP loan to defer payment of all or part of your student contribution.
Scholarship options
A Deakin scholarship can open the door to new opportunities. Whether you have something unique to offer or simply need a bit of extra support to reach your goals, we’re here to help. Scholarships can assist with course fees, living costs and study materials – so you can focus on achieving your best. Explore the range of opportunities and find the right fit for you.
Deakin alumni discount
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.
Apply now
Apply directly to Deakin
To apply, create an account in the Deakin Application Portal, enter your personal details and 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.
Research information
Students interested in pursuing a Higher Degree by Research (HDR), including a Masters by Research or PhD are encouraged to undertake the Professional Studies – Research Project pathway. High achieving students with a particular interest in research should also consider undertaking either the Research Training in Information Technology specialisation or additional research units as electives (e.g. SIT724, SIT746 and/or SIT747). Students are encouraged to contact Student Central and speak to a course adviser if they are interested in pursuing this option.
Pathways
Pathways for students to enter the Master of Data Science (Professional) are as follows:
- Graduate Certificate of Information Technology (S578) followed by a 16-credit-point Master of Data Science (Professional)
- Graduate Certificate of Information Technology (S578) and Graduate Certificate of Data Analytics (S576) followed by a 12-credit-point Master of Data Science (Professional)
Pathway options will depend on your professional experience and previous qualifications.
Alternate exits
- Graduate Certificate of Data Analytics (S576)
- Graduate Diploma of Data Science (S677)
- Master of Data Science (S777)
Career outcomes
In fiercely competitive markets where businesses are constantly striving to increase profit, reduce costs and provide exceptional customer value, the need for skilled data professionals is growing at a rapid pace. Graduates of this course 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 or marketing specialist.
Professional recognition
The Master of Data Science (Professional) is professionally accredited with the Australian Computer Society (ACS). This course is recognised internationally for entry to professional practice by other accrediting bodies through the Seoul Accord.
In order to meet ACS requirements for professional membership, students must satisfy the completion requirements for the whole degree. In addition, ACS guidelines require that the following specific units are completed at Deakin or equivalent units undertaken within another ACS-accredited program: SIT731, SIT743, SIT744, SIT753, SIT764, SIT782, SIT723, SIT792, SIT791, SIT709.
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.
| Course Learning Outcomes |
|---|
| Develop a broad, coherent knowledge of the analytics discipline, including: the origin and characteristics of data; the methods and approaches to dealing with data appropriately and securely; and how the use of analytics outcomes can be used to improve business, organisations or society. Apply advanced knowledge and skills to decompose complex processes (from real world situations) to develop data analytics solutions for use in modern organisations across multiple industry sectors. Assess the role data analytics plays in the context of modern organisations and society in order to add value. Have a broad appreciation of advanced topics within the IT domain through engagement with research or specialist studies. |
| Communicate in professional and other context to inform, explain and drive sustainable innovation through data science and to motivate and effect change by drawing upon advances in technology, future trends and industry standards, and by utilising a range of verbal, graphical and written methods, recognising the needs of diverse audiences including specialist and non-specialist clients, industry personnel and other stakeholders. |
| Identify, evaluate, select and use advanced digital technologies, platforms, frameworks, and tools from the field of data science to generate, manage, process and share digital resources and justify digital tools selection to influence others. |
| Questions assumptions and seeks to uncover inconsistencies and ambiguities in information and judgements, critically evaluates their sources and rationales, to inform and justify decision making in the field of data science. |
| Demonstrate an advanced and integrated understanding of data science and apply expert, specialised cognitive, technical, and creative skills from data science to understand requirements and design, implement, operate, and evaluate solutions to complex real-world and ill-defined computing problems. |
| Apply reflective practice and work independently to apply knowledge and skills in a professional manner to complex situations and ongoing learning in the field of data science with adaptability, autonomy, responsibility, and personal and professional accountability for actions as a practitioner and a learner. |
| Work independently and collaboratively within multidisciplinary environments to achieve team goals, contributing specialist knowledge and skills from data science to advance the teams objectives, employing effective teamwork practices and principles to cultivate creative thinking, interpersonal adeptness, leadership skills, and handle challenging discussions, while excelling in diverse professional, social, and cultural scenarios. |
| Engage in professional and ethical behaviour in the field of data science, with appreciation for the global context, and openly and respectfully collaborate with diverse communities and cultures. |
Note – From 2026, Deakin commenced introducing Graduate Attributes (GAs), which define the distinctive characteristics of a Deakin graduate. You may notice some courses still refer to Graduate Learning Outcomes (GLOs) during this transition period.
*Deakin references data from a range of government, higher education and reputable media sources. Learn more about our achievements on our University rankings page, or explore our sources page for supporting references.
