Deakin University
Master of Data Science (Professional)
- Delivery: Face to Face
- Study Level: Postgraduate
- Duration: 24 months
- Course Type: Master's
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.
Course overview
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.
CSP Subsidised Fees Available
This program has a limited quota of Commonwealth Supported Places (CSP). The indicative CSP price is calculated based on first year fees for EFT. The actual fee may vary if there are choices in electives or majors.
Key facts
What you will study
To complete the Master of Data Science (Professional), students must pass 16 credit points.
The course is structured in four parts:
- Part A: Fundamental data science studies (four credit points)
- Part B: Mastery data science studies (four credit points)
- Part C: Specialisation (four credit points) or course elective units (four credit points)
- Part D: Professional studies (four credit points)
- Academic Integrity and Respect at Deakin Module (zero-credit-point compulsory unit)
- Academic Integrity and Respect at Deakin (Zero credit points)
- Real World Analytics
- Data Wrangling
- Mathematics for Artificial Intelligence
- Machine Learning
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.
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).
* Related to the broad field of Information Technology.
English language proficiency requirements
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.
Recognition of Prior Learning
Deakin 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.
Recognition of prior learning may be granted for relevant postgraduate studies, in accordance with standard University procedures.
Visit their website or contact the university for more information.
Outcomes
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.
- 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.
Fees and CSP
Estimated tuition fee in 2025: $8,802 (Commonwealth Supported Place)
All costs are calculated using current rates and are based on a full-time study load of eight credit points (normally eight units) per year.
A student’s annual fee may vary in accordance with:
- The number of units studied per term.
- The choice of major or specialisation.
- Choice of units.
- Credit from previous study or work experience.
- Eligibility for government-funded loans.
Student fees shown are subject to change. Contact the university directly to confirm.
Commonwealth Supported Places (CSP)
The Australian Government allocates certain numbers of CSP to universities each year, which are then distributed to students based on merit.
If you're a Commonwealth Supported Student (CSS), you'll only need to pay a portion of your tuition fees. This is known as the student contribution amount – the balance once the government subsidy is applied. This means your costs are much lower.
Limited CSP spaces are offered to students enrolled in selected postgraduate courses.
Your student contribution amount is:
- Calculated per unit you're enrolled in.
- Dependent on the study areas they relate to.
- Reviewed and adjusted each year.
HECS-HELP loans are available to CSP students to pay the student contribution amount.