Master of Data Science


Program Description

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 organizations around the world is how to harness ever-increasing volumes of data as an asset.

The Master of Data Science provides students with the knowledge and skills to understand and apply appropriate analytical methodologies to transform the way an organization achieves its 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, visualization, internet-based applications, and software project management. Students will also acquire essential skills in high-performance computing.

Course structure details


Students who have completed degree studies in a non-cognate area, or equivalent as recognized by the Faculty, must complete relevant conversion units up to the value of 24 points from this group, as advised by the Faculty.
  • CITS1401 Problem Solving and Programming (6)
  • CITS1402 Relational Database Management Systems (6)
  • CITS2401 Computer Analysis and Visualisation (6)
  • STAT1400 Statistics for Science (6)
  • STAT1520 Economic and Business Statistics (6)
  • STAT2401 Analysis of Experiments (6)
  • STAT2402 Analysis of Observations (6)


Take all units (36 points):
  • CITS4009 Introduction to Data Science (6)
  • CITS5503 Cloud Computing (6)
  • CITS5504 Data Warehousing (6)
  • CITS5508 Advanced Data Mining (6)
  • STAT4064 Applied Predictive Modelling (6)
  • STAT4066 Bayesian Computing and Statistics (6)

Option - Group A

Take unit(s) to the value of 36 points, including a minimum of 18 points at Level 5.
  • CITS4008 Scientific Communication (6)
  • CITS4402 Computer Vision (6)
  • CITS4403 Computational Modelling (6)
  • CITS4404 Artificial Intelligence and Adaptive Systems (6)
  • CITS4407 Open Source Tools and Scripting (6)
  • CITS4419 Mobile and Wireless Computing (6)
  • CITS5011 Data Science Research Project Part 1 (6)
  • CITS5012 Data Science Research Project Part 2 (6)
  • CITS5013 Data Science Research Project Part 3 (12)
  • CITS5505 Agile Web Development (6)
  • CITS5506 The Internet of Things (6)
  • CITS5507 High-Performance Computing (6)
  • GENG5505 Project Management and Engineering Practice (6)
  • INMT5526 Business Intelligence (6)
  • MGMT5504 Data Analysis and Decision Making (6)
  • PUBH5769 Biostatistics II (6)
  • PUBH5802 Advanced Analysis of Linked Health Data (6)
  • STAT4063 Computationally Intensive Methods in Statistics (6)
  • STAT4065 Multilevel and Mixed-Effects Modelling (6)
  • STAT4067 Applied Statistics and Data Visualisation (6)

Admission Requirements

Last updated Mar 2020

About the School

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