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postgraduate

Degree

Master of Data Science (Coursework)

Course code: #MA-DATASC

postgraduate

Degree

Master of Data Science (Coursework)

Quick facts

  • Annual tuition (2022)

    $38,600 AUD

  • Application fee

    Free

  • Duration

    2 years

  • PSW

    2 years

  • Min GPA

    50 out of 100

  • CRICOS code

    099117B

Options
Project

These items are optional and you can choose them as you wish after applying for the course.

Deadlines

Term start& deadline Deadline
Fall-February 22-February-2023 2023-02-22
Winter-July 26-July-2023 2023-07-26
Fall-February 22-February-2024 2024-02-22
Winter-July 26-July-2024 2024-07-26

Overview

Master of Data Science

The Master of Data Science at the Swinburne University of Technology is designed to prepare students to work at 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, and develop skills in state-of-the-art techniques and contemporary tools covering the entire data management lifecycle.

Estimate your cost

Residency
Count of person

$50,700

Total costs

yearly

Details


Cost of living 1 person $10,212
Accommodation 1 bed room $12,100
Tuition 1 person $38,600

Hourly wage

Min wage

23.23 AUD / 1 hour

in Australia every student can work 48 hour per fortnight

Required documents

  • Academic transcripts
  • Award certificates
  • A key/guide to the grading system
  • Evidence of work experience (i.e. a resume and statement of employment from your employer)
  • Official English language translations of any documents not in English
  • Evidence of your English language proficiency

Language requirements

GRE
not required
GMAT
not required

IELTS

6.5
6
listening
6
writing
6
speaking
6
reading

TOEFL

79
12
listening
21
writing
18
speaking
13
reading

PTE

58
50
listening
50
writing
50
speaking
50
reading

Cambridge

176
169
listening
169
writing
169
speaking
169
reading
Language pathway (conditional offer) is available

Swinburne English Language Intensive Course for Overseas Students (ELICOS) is designed to help you improve your English language skills to study or progress your career.

Swinburne offers two types of English language courses: General English and English for Academic Purposes.

General English is designed to improve your language skills for day-to-day situations. It can also prepare you for further English language studies.

English for Academic Purposes is designed to teach you the language skills needed to study at university. 

It can help you meet the minimum English language entry requirements for entry to your chosen course at Swinburne.

Prerequisites:

IELTS or equivalent

LevelApproximate entry levelLead to
Advanced (EAP)IELTS 5.5 - 6.0 or equivalentEAP 5 - Higher Education - Undergraduate & Postgraduate
Upper-intermediate (EAP)IELTS 5.5 or equivalentEAP 4
IntermediateIELTS 5.0 or equivalentGE 3 - EAP 3
Pre-intermediateIELTS 4.5 or equivalentGE 2
Elementary       IELTS 3.5 or equivalentGE 1

Academic background and requirement

The admission requirements for a Master of Data Science consist of:

  • a completed bachelor's degree (or higher award) in any discipline from a recognised higher education institution or equivalent
  • successful completion of the Postgraduate Qualifying Program at Swinburne

Postgraduate Qualifying Program

The Postgraduate Qualifying Program (PQP) prepares students who do not meet Swinburne's English language and/or academic entry requirements to undertake postgraduate study at Swinburne.

Successful completion of this program offers guaranteed entry to the first year of a postgraduate degree or double degree at Swinburne.

Career opportunities

  • Data Analyst
  • Data Scientist
  • Database Administrator
  • Developer
  • Information Officer
  • Statistician

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