Master of Data Science (Professional)
2025 Deakin University Handbook
| Year | 2026 course information |
|---|---|
| Award granted | Master of Data Science (Professional) |
| Deakin course code | S770 |
| Course Credit Points | 16 |
| Course version | 1 |
| Faculty | Faculty of Science, Engineering and Built Environment |
| Course Information | For students who commenced from 2022 onwards |
| Campus | Offered at Burwood (Melbourne), Online |
| Duration | 2 years full-time or part-time equivalent |
| Course Map - enrolment planning tool | These course maps are for new students commencing from Trimester 1 2026:
These course maps are for new students commencing from Trimester 2 2026:
Course maps for commencement in previous years are available on the Course Maps webpage or please contact a Student Adviser in Student Central. |
| CRICOS code | 107030E Burwood (Melbourne) |
| Australian Qualifications Framework (AQF) recognition | The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 9 |
Course sub-headings
- Course overview
- Indicative student workload
- Professional recognition
- Career opportunities
- Participation requirements
- Mandatory student checks
- Pathways
- Alternative exits
- Research information
- Course Learning Outcomes
- Course rules
- Course structure
- Work experience
- Details of specialisations
- Fees and charges
Course overview
The sheer volume and complexity of data available to businesses today presents challenges tomorrow's graduates must be ready to solve. Modern organisations are placing increasing emphasis on the use of data to inform both day-to-day operations and long-term strategic decisions. You will explore the various origins of data and the methods to manage, organise and manipulate data within regulatory, ethical and security constraints.
The Master of Data Science (Professional) equips you with specialised skills in data science and offers you the chance to engage in industry-based learning or a research project supervised by our internationally recognised staff. With a growing demand for data specialists in every sector, you will be equipped with the skills to optimise performance and add a competitive advantage.
Want to take your career to the next level with specialised study?
Develop specialised expertise in categorising and transferring raw data into meaningful information for the benefit of prediction and robust decision-making. You will gain the technical skills to harness the power of data through artificial intelligence and machine learning, developing innovative solutions to the challenges faced by industry and governments.
This course focuses on developing skills in data science, data modelling and design, machine learning, programming and software development. You will develop expert knowledge of these technical aspects of data science as well as in-depth skills in your chosen area of specialisation.
Indicative student 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.
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.
Career opportunities
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 advisor, management analyst, business advisor and strategist, marketing manager, market research analyst or marketing specialist.
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.
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.
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)
- Graduate Diploma of Data Science (S677) followed by an 8-credit-point Master of Data Science (Professional)
Pathway options will depend on your professional experience and previous qualifications.
Alternative exits
| Graduate Certificate of Data Analytics (S576) | |
| Graduate Diploma of Data Science (S677) | |
| Master of Data Analytics (S777) |
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.
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 advisor if they are interested in pursuing this option.
Course Learning Outcomes
| Deakin Graduate Learning Outcomes | Course Learning Outcomes |
|---|---|
| Discipline-specific knowledge and capabilities | 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. |
| Communication | 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. |
| Digital literacy | 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. |
| Critical thinking | 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. |
| Problem solving | 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. |
| Self-management | 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. |
| Teamwork | 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. |
| Global citizenship | 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. |
Course rules
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.
Course structure
Part A: Fundamental Data Science studies
| DAI001 | Academic Integrity and Respect at Deakin (0 credit points) |
| SIT718 | Real World Analytics |
| SIT731 | Data Wrangling |
| SIT787 | Mathematics for Artificial Intelligence |
| SIT720 | Machine Learning |
Part B: Mastery Data Science studies
| SIT741 | Statistical Data Analysis |
| SIT742 | Modern Data Science |
| SIT743 | Bayesian Learning and Graphical Models |
| SIT744 | Deep Learning |
Part C: Specialisation or Course elective units
A 4 credit point specialisation or 4 level 7 SIT or MIS-coded elective units (excluding SIT771, SIT772, SIT773 and SIT774).
Refer to the details of each specialisation for availability.
- AI and Computer Vision
- Analytics in Internet of Things
- Blockchain and Software Development
- Business Analytics
- Cyber Security
- Information Systems
- Information Technology Research Training
- Networking and Cloud Technologies
Part D: Professional studies
Team Project
| SIT753 | Professional Practice in Information Technology |
| SIT764 | Team Project (A) - Project Management and Practices (capstone) |
| SIT782 | Team Project (B) - Execution and Delivery (capstone) |
1 level 7 SIT or MIS-coded elective (1 credit point)~
OR
Professional Practice
| STP710 | Career Tools for Employability (0 credit points) |
| SIT753 | Professional Practice in Information Technology |
| SIT764 | Team Project (A) - Project Management and Practices (capstone) |
| SIT791 | Professional Practice (2 credit points) * (capstone) |
OR
Research Project^
| SIT753 | Professional Practice in Information Technology |
| SIT764 | Team Project (A) - Project Management and Practices (capstone) |
Plus 1 unit (2 credit points) from the following:
| SIT723 | Research Techniques and Applications (2 credit points) + (research training capstone) |
| SIT792 | Minor Thesis (2 credit points) + (research training capstone) |
*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 advisor if they are interested in pursuing this option.
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.
Details of specialisations
Cyber Security
Campuses
Burwood (Melbourne), Online
Unit set code
SP-S000028
Overview
Develop skills in securing data, communications and infrastructure , as well as investigating, analysing and providing solutions to computer crime. You will gain problem-solving, communication and technical capabilities related to information technology security, along with an understanding of the legal, regulatory and ethical contexts in which these skills are used. Security units provide a solid foundation in areas including information security, internet and network security, access controls and firewalls.
Units
| SIT716 | Computer Networks and Security |
| SIT704 | Ethical Hacking |
And two (2) units from the following:
| SIT703 | Computer Forensics and Investigations |
| SIT735 | Application and Communication Protocol Security |
| SIT736 | Identity, Access Management and Physical Security |
| SIT738 | Secure Coding |
| SIT763 | Cyber Security Management |
S770 Master of Data Science (Professional) students wishing to undertake this specialisation may be required to complete units in Trimester 3, depending on the professional studies option they choose.
AI and Computer Vision
Campuses
Online
Unit set code
SP-S000093
Overview
Artificial intelligence (AI) is rapidly becoming essential to technological advancement across industries and is projected to contribute up to $15.7 trillion to the global economy by 2030. This specialisation will equip you with the knowledge and skills to design, develop and deploy AI solutions that enhance business operations. You will explore key areas including computer vision, speech processing and human-aligned AI.
Units
Any 4 units from the following:
| SIT788 | Engineering AI Solutions |
| SIT789 | Robotics, Computer Vision and Speech Processing |
| SIT796 | Reinforcement Learning |
| SIT799 | Human Aligned Artificial Intelligence |
| SIT770 | Natural Language Processing |
S770 Master of Data Science (Professional) students wishing to undertake this specialisation may be required to complete units in Trimester 3, depending on the professional studies option they choose.
Analytics in Internet of Things
Campuses
Burwood (Melbourne), Online
Unit set code
SP-S000094
Overview
There is a growing demand for Internet of Things (IoT) related skillsets in the IT job market. Many organisations are starting to realise the enormous potential of IoT in their business - however, they also acknowledge the major shortage of experts who are skilled in this domain. This specialisation will help equip you with the ability to design and deploy safe, secure and successful IoT solutions to meet business needs.
Units
| SIT725 | Applied Software Engineering |
| SIT729 | Software Architecture and Scalability for Internet of Things |
| SIT730 | Embedded Systems Development |
Plus one unit in:
| SIT722 | Software Deployment and Operation |
| SIT732 | Developing Secure Internet of Things Applications |
Blockchain and Software Development
Campuses
Burwood (Melbourne), Online
Unit set code
SP-S000092
Overview
This specialisation introduces you to state-of-the-art blockchain technologies and allows you to explore various software platforms and tools used for large-scale data analysis. You will learn how to build software solutions using modern software engineering techniques. Additionally, you can choose to hone your studies in the design and development of cloud applications or blockchain technologies, depending on your area of interest.
Units
| SIT708 | Mobile Application Development |
| SIT725 | Applied Software Engineering |
| SIT728 | Blockchain Technologies and Real-World Applications |
| SIT737 | Cloud Native Application Development |
Business analytics
Campuses
Burwood (Melbourne), Online
Unit set code
SP-MDBS004
Units
| MIS770 | Foundation Skills in Data Analysis |
| MIS771 | Descriptive Analytics and Visualisation |
Plus 2 credit points from:
| MIS772 | Predictive Analytics |
| MIS714 | People Analytics |
| MIS781 | Business Intelligence and Database |
Information Systems
Campuses
Burwood (Melbourne), Online
Unit set code
SP-MDBS012
Units
Any 4 units from the following:
| MIS701 | Digital Business Analysis |
| MIS712 | Managing Digital Transformation |
| MPE701 | Information Technology, Markets and Business Strategy |
| MIS761 | Cyber Security Strategies |
| MIS782 | Value of Information |
Information Technology Research Training
Campuses
Burwood (Melbourne), Waurn Ponds (Geelong), Online
Unit set code
SP-S000011
Overview
The information technology research training specialisation is ideally suited to students who are interested in pursuing a higher degree by research (HDR), including a masters by research or PhD. This specialisation includes four credit points of dedicated research training to support student preparedness for an HDR.
Units
4 credit points from:
| SIT723 | Research Techniques and Applications (2 credit points)^* |
| SIT724 | Research Project (2 credit points)* |
| SIT746 | Research Project (Advanced) (2 credit points)* |
| SIT747 | Research Project (Publication) (2 credit points)* |
| SLE761 | Professional Research Practice |
1 level 7 SIT or MIS elective unit (1 credit point)
^Students who have completed SIT723 as part of the Professional Studies Research Project option should complete 4 credit points from SIT724, SIT746, SIT747, SLE761 and 1 level 7 SIT or MIS elective unit.
* Entry is subject to specific unit entry requirements.
Networking and Cloud Technologies
Campuses
Burwood (Melbourne), Online
Unit set code
SP-S000021
Overview
Learn to take advantage of modern networking and cloud technologies in the development, deployment, and scaling of enterprise solutions.
Units
Any four (4) units from the following:
| SIT706 | Cloud Computing |
| SIT716 | Computer Networks and Security |
| SIT727 | Cloud Automation Technologies |
| SIT722 | Software Deployment and Operation |
| SIT737 | Cloud Native Application Development |
S770 Master of Data Science (Professional) students wishing to undertake this specialisation may be required to complete units in Trimester 3, depending on the professional studies option they choose.
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.
Fees and charges
Tuition fees will vary depending on the type of fee place you hold, your course, your commencement year, the units you choose to study, your study load and/or unit discipline.
Your tuition fees will increase annually at the start of each calendar year. All fees quoted are in Australian dollars ($AUD) and do not include additional costs such as textbooks, computer equipment or software, other equipment, mandatory checks, travel, consumables and other costs.
For further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods visit our Current students website.
Further information
Contact Student Central for assistance in course planning, choosing the right units and explaining course rules and requirements. Student Central can also provide information for a wide range of services at Deakin. To help you understand the University vocabulary, please refer to our Enrolment codes and terminology page.