Master of Data Science (Professional)

2025 Deakin University Handbook

Year	2025 course information
Award granted	Master of Data Science (Professional)
Deakin course code	S770
Faculty	Faculty of Science, Engineering and Built Environment
Campus	Offered at Burwood (Melbourne)
Online	Yes
Duration	2 years full-time or part-time equivalent
Course Map - enrolment planning tool	The course map for new students commencing from Trimester 1 2025. Professional Studies (Professional Practice) Professional Studies (Team Project) Professional Studies (Research Project) Course maps for commencement in previous years are available on the Course Maps webpage or please contact a Student Adviser in Student Central.
CRICOS course 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

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 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.

Develop specialised skills 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 being faced by industry and governments. 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?

The Master of Data Science (Professional) builds on the specialised skills from the Master of Data Science, offering you the chance to engage in industry-based learning or a research project supervised by our internationally recognised staff.

You will also have the opportunity to hone your skills in a specialisation of your choosing, with options such as cyber security, blockchain and software development, networking and cloud technologies, AI and more.

You will develop expert knowledge of the 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.

Career opportunities

In fiercely competitive markets where businesses are constantly striving to increase profit, reduce costs and provide exceptional customer value, the requirement 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 a 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)

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

To complete the Master of Data Science (Professional) students must pass 16 credit points and meet the following course rules to be eligible to graduate:

DAI001 Academic Integrity and Respect at Deakin (0-credit-point compulsory unit) in their first study period
Part A: Fundamental Data Science studies:
- 4 credit points of core units
Part B: Mastery Data Science studies:
- 4 credit points of core units
Part C: Specialisation or course electives:
- 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
Part D: Professional studies:
- 4 credit points of professional studies units (excluding SIT771, SIT772, SIT773 and SIT774)

Students are required to meet the University's academic progress and conduct requirements. See the enrolment codes and terminology to help make sense of the University’s vocabulary.

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.

Part D: Professional studies

Team Project

SIT753

Professional Practice in Information Technology

SIT764

Team Project (A) - Project Management and Practices

SIT782

Team Project (B) - Execution and Delivery

1 level 7 SIT or MIS-coded elective (1 credit point)~

Professional Practice

STP710

Career Tools for Employability (0 credit points)

SIT753

Professional Practice in Information Technology

SIT764

Team Project (A) - Project Management and Practices

SIT791

Professional Practice (2 credit points)*

Research Project^

SIT753

Professional Practice in Information Technology

SIT764

Team Project (A) - Project Management and Practices

Plus 1 unit (2 credit points) from the following:

SIT723

Research Techniques and Applications (2 credit points)+

SIT792

Minor Thesis (2 credit points)+

*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 an understanding of problem-solving, communication and technical capabilities related to information technology security and the legal, regulatory and ethical contexts in which these skills are used. The 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 for 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 knowledge and skills in computer vision, speech processing, human aligned AI, and the design, development and deployment of AI solutions to enhance business operations.

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

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

MIS701

Digital Business Analysis

MIS761

Cyber Security Strategies

MIS770

Foundation Skills in Data Analysis

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

Course duration

Course duration may be affected by delays in completing course requirements, such as failing of units or accessing or completing placements.

Further information

Student Central can help you with course planning, choosing the right units and explaining course rules and requirements.

Contact Student Central

Fees and charges

Fees and charges vary depending on the type of fee place you hold, your course, your commencement year, the units you choose to study, and their study discipline or your study load.

Tuition fees increase at the beginning of each calendar year and all fees quoted are in Australian dollars ($AUD). Tuition fees do not include textbooks, computer equipment or software, other equipment or costs such as mandatory checks, travel and stationery.

Estimate your fees

For further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods visit our Current students website.