Top 150 worldwide for computer science
Accredited by Australian Computer Society (ACS)
#1 Victorian university for computing median salary
Why choose data science (professional) at Deakin
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.
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Professional accreditation and global recognition
Graduate with a degree accredited by the Australian Computer Society (ACS) and recognised worldwide through the Seoul Accord.
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Career-ready data science capability
Graduate with strong skills in data science, machine learning and analytics, ready to interpret data and support decision-making across industries.
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Flexible professional pathways
Choose a team-based project, industry placement or research project to apply your skills in a way that suits your career goals.
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Strong global demand for data skills
Big data specialists are among the fastest-growing roles globally, with data analysts and scientists also ranking in the top 12.
Connected to industry
Deakin’s strong industry connections help shape your learning. Build practical experience in real workplace contexts through work-integrated learning, mentoring and networking opportunities. Industry advisory boards also help shape our degrees, which means what you study is current, relevant and aligned to what your future employers need.
Deakin puts employability first
Career outcomes
Build specialist data skills and practical experience to help you stand out in competitive industries. You could pursue careers spanning data science and analytics, business consulting, management, strategy and marketing.
Data scientist
Analyse large and complex datasets to uncover insights, build predictive models and solve business problems. Apply statistical analysis, machine learning and programming skills to support data-driven decision-making.
- $125K
Typical annual salary in Australia
- 4.2/5
Job satisfaction
Data analyst
Collect, prepare and interpret data to identify trends and provide actionable insights. Work with stakeholders to help organisations make informed decisions using evidence-based analysis and reporting.
- $105K
Typical annual salary in Australia
- #11
Fastest-growing job globally
Other jobs
- Analytics programmer
- Analytics consultant
- Analytics manager
- Business analyst
- Market research analyst
- Marketing specialist
Key dates
Direct applications
Trimester 3 2026 applications close 18 October 2026
Trimester 1 2027 applications close 7 February 2027
FAQs
A Deakin postgraduate degree can help you advance your career, deepen your expertise in a specialist field, pivot into a new industry and stand out in a competitive job market. Every course is built with industry input and taught by academics who are active practitioners, so the skills you gain are immediately applicable. Postgraduate study at Deakin is also your chance to connect with leaders in your field and build a network of industry contacts who become valuable professional connections, giving you an advantage that goes well beyond the qualification itself.
Most Deakin postgraduate courses are fee-paying, but there are practical ways to manage the cost of study. You can defer fees with a FEE-HELP loan, repaid through the ATO once you earn above the income threshold. A number of courses have Commonwealth Supported Places where the government covers part of your tuition. Deakin scholarships recognise academic achievement, professional experience and financial need. If you've studied at Deakin before, you may be eligible for a 10% alumni discount. Recognition of prior learning can also reduce costs by crediting past study so you finish sooner.
Yes to all three. Most Deakin postgraduate degrees can be studied online, on campus or a blend of both, and you may be able to switch between full and part time at the start of each trimester to suit your life. If you want to move faster, select courses offer a one-year masters degree designed for working professionals. With three start dates each year for most courses – March, July and November – you don't have to wait long to begin.
The main differences are depth, duration and career outcomes. A graduate certificate is a short, focused qualification, typically six months full time, ideal for upskilling quickly in a specific area. A graduate diploma offers broader knowledge or supports a career change, usually one-year full time. A masters degree delivers advanced expertise and professional recognition, typically one to two years full time. You can also stack qualifications – complete a graduate certificate and use the credit towards a masters.
Each Deakin postgraduate course has a unique structure, check the course stucture section of the course page to see compulsory units, electives and any specialisation streams available. All courses are shaped by industry, so content reflects real challenges in your field. Many courses let you tailor your studies through elective units or specialisations, and some include a capstone project where you apply your learning to a genuine workplace problem.
Entry requirements vary by course, so check this tab on the course page for specific criteria. Most Deakin postgraduate courses require a relevant bachelor degree, though some may accept significant demonstrable work experience as an alternative. You may also be able to build eligibility through a graduate certificate or graduate diploma, which in many cases could count towards a masters degree.
Deakin postgraduate courses are built with industry input, so you're learning skills employers are actively looking for. Depending on your course, you may access work-integrated learning through placements, internships or industry projects with partners including Microsoft, KPMG, National Australia Bank and the Geelong Cats Football Club. DeakinTALENT, Deakin's career service, supports you throughout your studies and for life, helping you grow your network and connect with opportunities in your field.
Yes. Recognition of prior learning (RPL) may turn your previous study or work experience into course credit, reducing both your study time and tuition costs. For some masters degrees, you may be able to receive credit for up to two-thirds of the course, if eligible. Use the RPL calculator to get an indication of what you might receive, and note that prior learning must generally be within the last 10 years, although some courses have a shorter time limit. You can apply for RPL as part of your course application.
*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.
What will I study in the Master of Data Science (Professional)?
This degree takes you from foundational technical skills to advanced, applied practice, building your ability to analyse, model and turn data into insights that inform decisions and solve problems.
Data science foundations
Establish core data capabilities
Learn programming, data wrangling and statistics while working with datasets to clean, transform and explore data for analysis.
Learn modelling and decision methods
Explore optimisation and machine learning approaches and apply models to tasks like classification, pattern discovery and resource allocation.
Work with modern data environments
Build skills in statistical modelling and data systems while analysing large datasets using advanced tools and considering ethics and privacy.
Advanced application, specialisation and professional study
Tailor your technical focus
Complete a specialisation or advanced electives to deepen expertise in a focus area or broaden your capability across data science fields.
Choose your professional pathway
Complete professional studies through a team project, industry placement or research project, each offering a distinct way to apply your learning.
Apply advanced skills in context
Work on complex challenges using contemporary tools and methods while building industry, project or research experience aligned to your pathway.
Course structure
To complete the Master of Data Science (Professional), you must pass 16 credit points.
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.
Are you a current student? For course information that applies to the year you started your degree, visit the handbook.
All students are required to meet the University's academic progress and conduct requirements
Units
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 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^
*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 and/or SIT747). Students are encouraged to contact Student Central and speak to a course adviser if they are interested in pursuing this option.
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.
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.
What to expect while studying
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.
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.
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.
Elective units may be selected that include compulsory placements, work-based training, community-based learning or collaborative research training arrangements.
You may have an opportunity to undertake a placement as part of your course. For more information, please visit deakin.edu.au/sebe/wil.
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 and/or SIT747). Students are encouraged to contact Student Central and speak to a course adviser if they are interested in pursuing this option.
At Deakin, we're committed to ensuring an inclusive environment that supports all students to belong, thrive and succeed. We work closely with students, where needed, to identify potential barriers to participation and where possible, provide tailored support so students can engage with learning and assessment activities.
If you are neurodivergent, have a disability, health condition or mental health condition that may impact your study or participation in university life, and want to know how Deakin could support you, contact our Domestic students (opens in a new window) or International students (opens in a new window) or Disability Resource Centre (opens email client) teams for a collaborative and confidential discussion. This discussion is to support you to make plans for your studies and future career and will not have any bearing on your application to the course.
When can I start?
When you study depends on your course, location and available intakes. Check the table to see when you can start and how study is offered throughout the year.
Your course learning outcomes describe the knowledge, skills and capabilities you’ll develop and be able to demonstrate by the time you graduate. Built into your course through your units and assessments, they provide a clear picture of what you’ll be equipped to know, understand and do – preparing you to apply your learning with confidence beyond university.
| 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. |
- Award granted
- Master of Data Science (Professional)
- Year
2027 course information
- Deakin code
- S770
- 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
Fees
Estimated tuition fee
$9,259
for 1 yr full-time - Commonwealth Supported Place (CSP)
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.
Check your eligibility or learn more about CSP or HECS-HELP.
Scholarships
We want to help you excel at Deakin. Our scholarships recognise your dedication and achievements, providing financial support that can ease the cost of living and studying. With less pressure, you'll have more freedom to focus on what matters most – your education and future success.
Applications for 2027 are open
Ready to take the next step? Apply now to start your journey at Deakin and get ready for what’s next.
Key dates
Direct applications
Trimester 3 2026 applications close 18 October 2026
Trimester 1 2027 applications close 7 February 2027
Apply now
Apply direct
Simply create an account in the Deakin Application Portal, enter your personal and educational details, upload your supporting documents and submit your application.
Recognition of prior learning
We value your previous study and experience. Recognition of prior learning enables you to get credit for what you've already achieved. When you apply, we'll consider your previous study and experience for recognition of prior learning.
Recognition of prior learning may be granted for relevant postgraduate studies, in accordance with standard University procedures.
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.
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.