Why Study / Key Benefits

The Bachelor of Data Science is designed for students who want to build technical and analytical skills for working with large datasets, data-driven decision-making and forecasting. The course combines programming, computing, databases, cloud computing, big data, data visualisation and software development with practical project work.

Key benefits include:

• Develops skills in computer software development, machine learning modelling and application, big data management, data visualisation and data-driven decision-making.
• Students complete six projects, one in each semester, with projects building progressively on earlier learning.
• Provides exposure to practical, industry-oriented data science projects.
• Offers opportunities to use contemporary data science tools and methods.
• Students can combine Data Science with a co-major, minor, advanced minor or electives from other disciplines.
• The course is accredited by the Australian Computer Society at professional level.
• Swinburne highlights applications of data science across government, marketing, finance, healthcare and other industries.

Programme Structure and Subjects / Topics

The programme consists of 300 credit points: 100 credit points of core units, 100 credit points from the Data Science major and 100 credit points of other approved study.

Core units:

• Introduction to Programming – COS10009
• Technology in an Indigenous Context Project – COS10025
• Networks and Switching – TNE10006
• Computer Systems – COS10004
• Web Technology Project – COS10026
• Object Oriented Programming – COS20007
• Computing Technology Project A – COS40005
• Computing Technology Project B – COS40006

Data Science major units:

• Data Science Principles – COS10022
• Database Design Project – COS20031
• Cloud Computing Architecture – COS20019
• Big Data Architecture and Application – COS20028
• Computing Technology Innovation Project – COS30049
• Data Visualisation – COS30045
• Software Architectures and Design – SWE30003
• Software Deployment and Evolution – SWE40006

Indicative 2026 study sequence:

Year 1:

Semester 1:

• Introduction to Programming
• Technology in an Indigenous Context Project
• Networks and Switching
• Data Science Principles

Semester 2:

• Computer Systems
• Web Technology Project
• Object Oriented Programming
• Elective

Year 2:

Semester 1:

• Database Design Project
• Three electives

Semester 2:

• Cloud Computing Architecture
• Big Data Architecture and Application
• Computing Technology Innovation Project
• One elective

Year 3:

Semester 1:

• Computing Technology Project A
• Data Visualisation
• Software Architectures and Design
• One elective

Semester 2:

• Computing Technology Project B
• Software Deployment and Evolution
• Two electives.

Disciplines / Specialisations

The principal discipline is Data Science.

Students complete the Data Science major and use the remaining 100 credit points for a co-major, minor, advanced minor and/or electives.

Available co-major options currently include areas such as:

• Accounting
• Advertising
• Animation
• Biotechnology
• Business Analysis
• Business Analytics and Analysis
• Computer Science
• Data Analytics
• Environmental Science
• Environmental Sustainability
• Finance
• Financial Planning
• Information Systems
• Logistics and Supply Chain Management
• Management
• Marketing
• Neuroscience
• Psychology
• Public Relations
• Social Media
• Space Technology

The handbook contains the complete current list and associated course rules.

Minor options include areas such as:

• Applied Mathematics
• Business Law
• Data Analytics
• Data Science
• Digital Advertising Technology
• Engineering
• Entrepreneurship
• Finance
• Health Statistics
• Human Resource Management
• Information Systems
• International Relations and Security
• Logistics and Supply Chain Management
• Management
• Marketing
• Media Industries
• Psychology
• Public Relations
• Social Media.

Programme Highlights

• 3-year bachelor degree.
• 300 credit points.
• Hawthorn campus, Melbourne.
• CRICOS code 109149G.
• ACS professional-level accreditation.
• Six progressive projects across the three-year course.
• Strong emphasis on programming, big data, machine learning, data visualisation and data-driven decision-making.
• Practical project experience through Work Integrated Learning.
• Option to undertake a 6-month or 12-month professional placement, subject to competitive selection and visa/course requirements.
• Flexible final-year study through co-majors, minors, advanced minors and electives.
• Recommended electives include areas such as artificial intelligence, data structures, mobile development, cybersecurity, business intelligence, mathematics, statistics and technology internships.

Career Outcomes

Swinburne identifies the following potential career outcomes:

• Data scientist
• Data analyst
• Business intelligence developer
• Data engineer
• Machine learning engineer
• Data warehouse architect
• Data infrastructure architect.

The programme develops capabilities applicable to data-driven roles involving:

• Data analysis
• Machine learning
• Big data
• Data visualisation
• Software development
• Database design
• Cloud computing
• Data-driven decision-making
• Technology projects
• Data infrastructure

Latest Updates / Special Requirements

• Current upcoming start dates are 1 March 2027 and 2 August 2027.
• Application deadlines are 24 February 2027 and 28 July 2027 respectively.
• CRICOS course code: 109149G.
• Course code: BA-DS.
• The course is professionally accredited by the Australian Computer Society.
• Mathematics is a prerequisite area; students who do not meet the applicable mathematics prerequisite may need MathsLink Methods.
• Maximum academic credit: 200 credit points, normally 16 units.
• Academic credit is normally limited to studies or experience completed within the preceding five years because of ACS accreditation requirements.
• Professional placements are competitively selected. International students may need to change courses to undertake a placement, and Swinburne advises them to consider visa and extended-duration implications.
• The course contains capability requirements covering areas such as critical thinking, digital literacy, numeracy, communication, teamwork and interpreting visual/data information. Reasonable adjustments may be possible for adaptable components. 

International Student Visa Requirements

The relevant Australian visa is the Student visa, subclass 500.

For this course, Swinburne states that international students in Australia holding Student visas must study full-time and on campus.

Key requirements include:

• Enrolment in a full-time CRICOS-registered course.
• A valid Confirmation of Enrolment (CoE).
• Overseas Student Health Cover (OSHC), unless an applicable exemption applies.
• Meeting the Genuine Student requirement.
• Meeting applicable health requirements.
• Meeting applicable character requirements.
• Providing the required identity and supporting documents.
• Demonstrating financial capacity when evidence is required.
• Meeting applicable Student visa English-language requirements or an exemption.
• Signing the Australian Values Statement if aged 18 or over.