Master of Data Science

The master of data science will equip you with a comprehensive suite of skills needed to manage, manipulate, analyse and visualise data, across a wide range of sectors including science, business, it, health care and government. Your studies will include a deep dive into areas such as artificial intelligent and machine learning, data analytics for cyber threat intelligence, experiment design and visualisation, programming and more. 

As a graduate, you will meet the AQF level 9 requirements, putting you in high demand. This includes high-level roles in data science, data engineering, business analytics, statistics or data warehouse operation.
The course is fully accredited by the Australian Computing Society (ACS) and the Statistical Society of Australia (SSA).

Course overview

• This course provides an opportunity for you to develop an advanced understanding of data science by incorporating and interpreting complex information, concepts and theories to relevant disciplines, using data science tools and methods to manage, process, and analyse data.
• Throughout the course, you will utilise your skills to handle large volumes of data, working with real-time data, cloud computing, unstructured data and statistical models. 
• As a graduate, you may work in data science related areas such as the health care, finance, government administration and IT industries.
• This course is also available as a graduate diploma option for domestic and international students.
• To review entry requirements and application details relevant to you, please indicate whether you are a domestic or international student by selecting the filter in the top right corner of the screen.

Career paths

• Business analyst
• Data warehouse operator
• Data engineer
• Data scientist
• Statistician

Year 1
Semester 1

• Data Science for All
• 15 credit points
• ITECH5007

Foundations of Programming (Masters)

• 15 credit points
• ITECH5104

Statistics and R

• 15 credit points
• STATS5000
• Prescribed Electives

Semester 2
Professional Research and Communication

• 15 credit points
• ITECH5500

Artificial Intelligence and Machine Learning

• 15 credit points
• ITECH7001
• Prescribed Electives

Year 2
Semester 1

Advanced Data Science Project 1

• 30 credit points
• DATSC5001

Experiment Design and Visualisation

• 15 credit points
• DATSC7003

Computational Methods for Data Analysis

• 15 credit points
• MATHS7002

Semester 2
Advanced Data Science Project 2

• 30 credit points
• DATSC5002

Data Analytics for Cyber Threat Intelligence

• 15 credit points
• ITECH7614

Regression and Multivariate Data Analysis

• 15 credit points
• STATS7101