Gain the skills to tackle big data challenges and compete in the digital realm.


A rapidly expanding field that shows no sign of slowing. Big data and analytics now drive and inform strategic decision making and innovation whether it is in relation to engineering, finance, health or other professional areas. The challenge for organisations around the world is how to harness ever increasing volumes of data as an asset.

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Course description, features and facilities

The Master of Data Science provides students with the knowledge and skills to understand and apply appropriate analytical methodologies to transform the way an organisation achieves its goals and objectives, to deal effectively with large data management tasks, to master the statistical and machine learning foundations on which data analytics is built, and to evaluate and communicate the effectiveness of new technologies.

Students will gain a detailed knowledge of contemporary data management and analysis technologies, including those for data collection and storage, visualisation, internet-based applications, and software project management.

Students will also acquire essential skills in high performance computing.

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Key to availability of units:
S1 = Semester 1; S2 = Semester 2; N/A = not available in 2017

All units have a value of six points unless otherwise stated.

Note: Units that are indicated as N/A may be available in 2018 or 2019.

Note: Students are advised to refer to the recommended study guides available on the ECM website.

Students who have completed degree studies in a non-cognate area, or equivalent as recognised by the Faculty, must complete relevant conversion units up to the value of 24 points from this group, as advised by the Faculty.

S1, S2CITS1401Problem Solving and Programming
S2CITS1402Relational Database Management Systems
S1, S2CITS2401Computer Analysis and Visualisation
S1, S2STAT1400Statistics for Science
S1, S2STAT1520Economic and Business Statistics
S1STAT2401Analysis of Experiments
S2STAT2402Analysis of Observations

Take all units (36 points):

S2CITS4009Introduction to Data Science
S2CITS5503Cloud Computing
S1CITS5504Data Warehousing
N/ACITS5508Advanced Data Mining
S2STAT4063Computationally Intensive Methods in Statistics
S1STAT4064Applied Predictive Modelling

Take unit(s) to the value of 36 points, including a minimum of 18 points at Level 5.

Note: Enrolment in the Data Science Research Project is by invitation only.

Group A

S1CITS4008Scientific Communication
S1CITS4402Computer Vision
S1CITS4403Computational Modelling
S2CITS4404Artificial Intelligence and Adaptive Systems
S1CITS4407Open Source Tools and Scripting
S2CITS4419Mobile and Wireless Computing
S1, S2CITS5011Data Science Research Project Part 1
S1, S2CITS5012Data Science Research Project Part 2
S1, S2CITS5013Data Science Research Project Part 3 (12 points)
S1CITS5505Agile Web Development
S2CITS5506The Internet of Things
S2CITS5507High Performance Computing
S1, S2GENG5505Project Management and Engineering Practice
S2INMT5526Business Intelligence
S1, S2MGMT5504Data Analysis and Decision Making
S2PUBH5769Biostatistics II
N/APUBH5802Advanced Analysis of Linked Health Data
S1STAT4065Multilevel and Mixed-Effects Modelling
S1STAT4066Bayesian Computing and Statistics
S2STAT4067Applied Statistics and Data Visualisation

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Career opportunities

The Master of Data Science prepares graduates for a career as a data science or data analyst providing them with the skills to tackle large data management and exploitation tasks.

An emerging industry, it is anticipated that there will be a global skills shortage for people with data science knowledge as reported and identified by the McKinsey Global Institute study (2011). The study predicts a shortfall by 2018 of nearly 140,000 to 190,000 data scientists and 1.5 million managers with the ability to use big data to make effective decisions in the United States alone.

The skills graduates obtain during the course will make them internationally mobile as data science expertise is required globally. Graduates will be able find employment in a large range of companies and organisations across the resources, finance, commerce and utility sectors. In Western Australia, Data Science graduates are required for specialised data mining within the resource sector.

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Further study opportunities

Further study will allow you to gain a qualification in Doctor of Philosophy (PhD). It will open up opportunities in academia and research to help you to pursue your goals in a wide range of careers, depending on your area of research.

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These pages are under review and are being updated.

Check the Entrance requirements

This course is available to Australian and international students.

On this page

  1. Admission Requirements
  2. English competency

Admission Requirements

To be considered for admission to this course an applicant must have a bachelor's degree, or an equivalent qualification, as recognised by UWA, the equivalent of a UWA weighted average mark of at least 65 per cent; and completed Mathematics Applications ATAR, or equivalent, as recognised by UWA.

English competency

Refer to the University's English Language Competence requirements
These pages are under review and are being updated.

How to apply

This course is available to Australian and international students.

On this page

  1. How to apply
  2. Fees
  3. Contact us

How to apply

Apply online!


Refer to the Fee Calculator for up to date course and unit costs.

Contact us

(+61 8) 6488 3939
Enquire on-line
Frequently Asked Questions
First Floor, Ken and Julie Michael Building
7 Fairway (corner Cooper Street)
Crawley, Perth
Western Australia 6009
Normal opening hours
Monday - Friday, 8.30am - 5pm (Western Standard Time)

Note: We can help with application-related enquiries. If you need further course-specific information, you may wish to contact the relevant Faculty or School.

About UWA
Find out what makes UWA an internationally recognised university.
Foundation and preparatory courses
There are a range of programs available to help give you the opportunity to gain the academic qualifications or prerequisites required for admission to UWA.
Social life on campus
There are over 20,000 students enrolled at UWA - lots of new friends not only from Perth and Western Australia but from all areas in Australia and around the world.
These pages are under review and are being updated.

Register for an information session in 2017

Prospects - online newsletter

Master of Data Science: the details

Available 2017
Locations offered
Attendance types
Part-time, Full-time
Delivery mode
Starting dates
Semester 1, Semester 2
Weekly first year time commitment
The estimated weekly time commitment is 12 hours per unit which includes contact hours, personal study and examinations.
Standard full-time completion
1.5-2 years of full-time study (depending on the requirement to include conversion units).
Maximum time to complete
5 years
Contact details: course information
ECM Student Office
Faculty of Engineering, Computing and Mathematics The University of Western Australia M054, 35 Stirling Highway Crawley WA 6009
+61 8 6488 3061
Course code