Master of Data Science
Blended learning – on-campus and digital learning
The Master of Data Science is designed to prepare students to work on the forefront of data-driven decision-making and forecasting.
Build on your existing undergraduate qualification and/or industry experience as you develop an in-depth understanding of activities and processes related to managing, interpreting, understanding and deriving knowledge from large data sets.
In this course, you’ll learn how to gain meaningful insight from data obtained from business, government, scientific and other sources. Expand your knowledge and understanding of computer science and data analytics, develop skills in state-of-the-art techniques and contemporary tools covering the entire data management lifecycle.
Every international student application is considered for a scholarship
Whether you’re living in Australia or overseas, you’re automatically considered for a scholarship of up to 75% off your course fees. Please check our updated entry requirements.
George Swinburne STEM Achievement Postgraduate Scholarship
Find out how you can receive 30% reduction in course fees for this course. Learn more.
Duration
2 Year/s
Intakes
Hawthorn (Semester 1, Semester 2) - View application and start dates
CRICOS code
099117B
Fees
A$37080 (annual for 2022)*
The indicative course fees shown in Course Search apply to international students for the relevant year only. They are based on a standard study load per year. However, please note that fees are assessed according to a student's study load in each semester, and variation to study load will result in an adjustment to tuition fees. All fees are subject to annual review and may be adjusted.
Course information in detail
- Course detail, course structure and units of study.
Course description
The Master of Data Science is designed for postgraduate students who wish to extend their knowledge of computer science and data analytics in order to be able to gain meaningful insights from data coming from a variety of sources (business, governments, science). Students will develop skills in state-of-the-art techniques and gain experience in contemporary tools covering a variety of aspects of the entire data management lifecycle, allowing them to work on the forefront of data-driven decision making and forecasting. This advanced postgraduate course will build on students’ cognate undergraduate qualifications or relevant industry experience by developing an in-depth understanding of the activities related to managing, interpreting, understanding and deriving knowledge from large data sets.
International students in Australia who hold student visas are required to study full-time and on campus. Courses that are taught entirely online are only available to international students studying outside Australia or those in Australia who are not on a student visa. Online courses are not available to international students in Australia who hold a student visa.
Course structure
- Twelve (12) core units (175 credit points)
- Two (2) electives (25 credit points)
Volume of Learning
The Master of Data Science consists of 200 credit points. Units normally carry 12.5 credit points. A standard annual full-time load comprises 100 credit points and a part-time load comprises 50 credit points. The volume of learning of the Master of Data Science is typically 2 years.
Maximum Academic Credit
The maximum level of credit that can be granted for the Master of Data Science is 100 credit points (normally eight units)
Units of study
Careers and graduate outcomes
- Career opportunities and course aims and objectives.
Career opportunities
Aims and objectives
| # | Description |
|---|---|
| CLO1 | Demonstrate and apply a coherent understanding of the concepts and practices within the field of Data Science as an effective member of diverse teams in a professional context |
| CLO2 | Critically analyse various Data Science scenarios, evaluate the existing knowledge base, and propose and justify effective and/or innovative solutions, including the choice of appropriate technology |
| CLO3 | Demonstrate personal discipline, scholarship of the field, critical thinking, and judgment by completing substantial projects with industry relevance |
| CLO4 | Communicate information proficiently to technical and non-technical audiences, including industry practitioners |
| CLO5 | Apply knowledge of research principles and methods to solve diverse Data Science problems from scenarios relevant to science and/or industry and critically reflect on the appropriateness of the solution |
| CLO6 | Reflect on, and take responsibility for their own learning, manage their own time and processes effectively by regularly reviewing personal performance as a means of managing continuing professional development |
Pathways and scholarships
- Scholarships.
Course fees and requirements
- Fees, entry requirements and English language requirements.
Course fees
Entry requirements
A prerequisite for many courses, the Pearson Test of English Academic (PTE Academic) can now be done on campus in Hawthorn at Room 132, Building TD. Book now or call +61 3 9214 3584 for more information.
- a completed bachelor degree (or higher award) in any discipline from a recognised higher education institution or equivalent
- successful completion of the Postgraduate Qualifying Program at Swinburne
English language requirements
Satisfactory completion of one of the following:
- IELTS overall band of 6.5 (Academic Module) with no individual band below 6.0
- Swinburne’s English for Academic Purposes (EAP 5 Advanced level) with overall 70%, all skills 65%
- Or equivalent measures available at English language requirements.
How to apply
Find out more
Tel: +61 3 9214 8444 (outside Australia)