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.
This course is accredited by the Australian Computer Society (ACS).
We are a member institution of AWS Academy
Swinburne Sydney offers AWS Academy Cloud Foundations as part of its Master of Information Technology (Professional Computing), Master of Information Technology, and Master of Data Science courses.
AWS Academy Cloud Foundations is a course developed and maintained by AWS.
2 years full-time
February 2023 | June 2023 | September 2023
Study feesSee ‘Course fees & requirements’ below
Course information in detail
- Course detail, course structure and units of study
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.
To qualify for the Master of Data Science, students must complete 200 credit points comprising:
- 12 x core units (175 credit points)
- 1 or 2 elective units (25 credit points in total)
The Graduate Diploma of Data Science is an Exit Award only (not by admission).
Units of study
Complete the following 12 units (175 credit points):
- COS60004 Creating Web Applications
- COS60008 Introduction to Data Science
- COS60009 Data Management for the Big Data Age
- COS60010 Technology Enquiry Project
- COS60011 Technology Design Project *
- COS70004 User-Centred Design
- COS70008 Technology Innovation Project *
- COS80001 Cloud Computing Architecture
- COS80023 Big Data *
- COS80025 Data Visualisation
- COS80027 Machine Learning *
- COS80029 Technology Application Project *
Complete 2 x 12.5 credit point units:
- COS70006 Object-Oriented Programming
- ICT80004 Internship Project **
- ICT80007 Research Paper
* Outcome units - matched exemptions are generally not granted for higher education outcome units.
** Unit available by application only – only one Industry Engagement elective unit may be undertaken.
Careers and graduate outcomes
- Career opportunities, course aims and objectives, graduate skills and professional recognition.
Graduates will have skills in state-of-the-art techniques and 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.
Aims and objectives
At the completion of the Master of Data Science course, graduates will be able to:
- 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
- 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
- demonstrate personal discipline, scholarship of the field, critical thinking, and judgment by completing substantial projects with industry relevance
- communicate information proficiently to technical and non-technical audiences, including industry practitioners
- 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
- 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.
At Swinburne scholarships are about providing opportunity, promoting equity and recognising excellence and achievement. Scholarships are available for both commencing and current students. Find out more about scholarships.
Course fees & requirements
- Fees, entry requirements and English language requirements
A$38,600 (annual, full-time for 2023)*
Students holding an international student visa are required to study full-time and on-site. Programs that are taught solely online are not available to onshore international students who hold an international student visa.
*Fees displayed are relevant to 2023 and are subject to annual review. Fees are based on a student’s study load in each semester
Fees are estimates for students commencing in 2023 only: Tuition fees as published are subject to change given individual circumstances at enrolment. These fees apply for units studied in 2023 only and may change for units studied in future years.
Applicants are required to have completed one of the following:
- a completed bachelor degree (or higher award) in any discipline from a recognised higher education institution or equivalent; or
- the Postgraduate Qualifying Program (available to International applicants only).
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 above
- or equivalent measures available at English Language requirements.