Why Study / Key Benefits

The Master of Data Science is a postgraduate programme designed to develop advanced knowledge and practical skills in data analytics, data modelling, machine learning, data management and data-driven decision-making.

Key benefits include:

• Develop advanced skills for analysing and extracting meaningful insights from data from multiple sources.
• Learn contemporary techniques and technologies used across the data management and analytics lifecycle.
• Build knowledge of mathematics, programming, statistics, data modelling and data transformation.
• Develop practical problem-solving and research skills for science and industry applications.
• Complete industry-based project work with external organisations or business clients.
• Gain opportunities to work on real-world data science problems through the compulsory technology application project.
• Students achieving a credit average may apply to undertake the Internship Project unit as an industry intern.
• The qualification is professionally accredited by the Australian Computer Society (ACS) at professional level.

Programme Structure and Subjects / Topics

The Master of Data Science requires 200 credit points.

Graduate Certificate stage

The first 100 credit points comprise eight core units:

• Creating Web Applications – COS60004
• Introduction to Data Science – COS60008
• Data Management for the Big Data Age – COS60009
• Technology Design Project – COS60011
• Programming Principles and Practices – COS60018
• Cloud Engineering – COS80001
• Data Visualisation – COS80025
• Advanced Threats in AI and Data Security – CYB70006.

Graduate Diploma stage

The next stage adds:

• Technology Innovation Research and Project – COS70008, 25 credit points
• Big Data – COS80023, 12.5 credit points.

The Technology Innovation Research and Project unit develops research, innovation and project-related capabilities relevant to technology and data science applications.

Master's stage

The master's stage adds:

• Machine Learning – COS80027, 12.5 credit points
• Technology Application Project – COS80029, 25 credit points
• Two approved electives, totalling 25 credit points.

Disciplines / Specialisations

The Master of Data Science is a single data science master's qualification and does not currently list formal named specialisations on the official course page.

Students can develop particular areas of interest through their elective choices and practical project work, including:

• Data science and analytics
• Machine learning
• Big data
• Data visualisation
• Cloud engineering
• Data management
• AI and data security
• Software development
• Internet security
• Technology research and innovation.

Programme Highlights

• Two-year postgraduate data science qualification.
• 200 credit points.
• Hawthorn campus in Melbourne.
• CRICOS registered: 099117B.
• ACS professional accreditation.
• Industry-based project learning.
• Mandatory industry-based project component.
• Practical exposure to data analytics, machine learning, big data and data visualisation.
• Cloud engineering and AI/data security included within the core curriculum.
• Opportunity to apply for an industry internship project where the student achieves the required credit average.
• Nested Graduate Certificate and Graduate Diploma exit awards are available within the course structure.

Career Outcomes

Swinburne identifies potential career roles including:

• Data Engineer
• Machine Learning Engineer
• Data Analyst
• Data Architect
• Junior Data Scientist
• Customer Support Analyst
• Business Analyst
• Business Analyst Consultant
• Statistician
• Data Consultant.

Latest Updates / Special Requirements

• The current CRICOS code is 099117B.
• The current course duration remains two years full-time or equivalent part-time.
• 2027 starts are currently listed for 1 March and 2 August.
• 2027 application deadlines are currently listed as 24 February and 28 July respectively.
• The course is professionally accredited by the Australian Computer Society at professional level.
• International students in Australia holding Student visas must study full-time and on campus.
• Industry-based project participation is mandatory.
• Students with a credit average may apply for the Internship Project unit, subject to the relevant requirements and approval.
• Maximum academic credit is 100 credit points, normally eight units, with study/experience normally required to have been completed within the previous five years because of ACS accreditation requirements.

International Student Visa Requirements

International students studying the Master of Data Science in Australia generally apply for the Australian Student visa, subclass 500.

Core visa requirements

The Department of Home Affairs requires Student visa applicants to:

• Be enrolled in an eligible course.
• Hold a valid Confirmation of Enrolment (CoE) when the visa is decided.
• Maintain appropriate Overseas Student Health Cover (OSHC), unless an exemption applies.
• Meet applicable health and character requirements.
• Meet the Genuine Student requirement.
• Meet financial-capacity requirements where evidence is required by the applicant's document checklist.