Master of Data Science

MA-DATASC Postgraduate Sydney CRICOS code: 099117B

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.

Important!

If you’re an international student living outside Australia, you can currently only study this course online from your home country. Before applying, please make sure you meet the minimum English language entry requirements (we now accept some take-home English tests).

Duration

2 years full-time or 4 years part-time

Intakes

June 2021 | September 2021

Study modes

Full-time, Part-time (part-time available to domestic students only)

Study fees

See ‘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.

Course structure

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.

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

Core units

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  *

Elective units

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.

Career opportunities

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.

Financial support

At Swinburne, scholarships are about providing opportunity, promoting equity and recognising excellence and achievement. Scholarships are available for both commencing and current students.

International students
With the George Swinburne postgraduate Scholarship, students could be paying 30% less for the course, if they pursue the Master of Data ScienceMaster of Information Technology, Master of Information Technology (Professional Computing), or Master of Construction and Infrastructure Management.

Terms and Conditions apply, learn more.

Domestic students
There are a number of scholarships available to domestic students. Contact us to find out more.

Course fees & requirements

- Fees, entry requirements and English language requirements

Course fees

International students

A$36,000 (annual for 2021)
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.

Students holding an international student visa are required to study full-time and on campus. Due to government regulations, industry-based learning (IBL) and work placement are not available to onshore international students unless it is a compulsory component of the program. Programs that are taught solely online are not available to onshore international students who hold an international student visa.

Domestic students

A$28,480 (annual; full-time for 2021)

FEE-HELP is a loan given to eligible full-fee paying higher education students to help pay part or all of their tuition fees. The Commonwealth Government pays the amount of the loan directly to Swinburne.

The total tuition fee is dependent upon the combination of units of study selected by the student. Fees are reviewed each year.

Entry Requirements

The admission requirements for Master of Data Science consist of:

  • a completed bachelor degree (or higher award) in any discipline from a recognised higher education institution or equivalent

English language requirements

International students 
Satisfactory completion of one of the following:

  • minimum IELTS overall band of 6.5 (Academic Module) with no individual band below 6.0
  • TOEFL iBT (internet-based) minimum score of 79 with a reading band no less than 18 and writing band no less than 20
  • Pearson (PTE) minimum score of 58 (no communicative skills less than 50)
  • any other equivalent assessment of English language proficiency.

Find out more about English Language requirements.

Domestic students
Applications may also be assessed for English language requirements. For any questions, contact us.