This is the most comprehensive data science program in Australia, which combines high-level analytical and technical skills with industry-specific knowledge and essential professional attributes.

The Master of Data Science is one of the few programs in the world to combine a cross-disciplinary education with direct industry contact and practical experience in the exciting field of data science. 

Study advanced topics from computing, statistics, and mathematics as well as your choice of electives from business, finance, health, or science. Across the program, you’ll learn how to make informed decisions in data-intensive environments.

Use relevant big data tools and technologies and develop essential knowledge about the ethical use of data, legal considerations, communication, and more. In your final year you’ll also complete projects relevant to industry.

Graduate with a combination of high-level technical skills and a capacity for creative and disruptive thinking. You’ll be ready to solve complex data science problems globally and meet the strong demand for expert data scientists.

Programme Structure
Part A – Compulsory

14 to 16 units including all of

Course Title
Introduction to Data Science
Responsible Data Science
Data Analytics at Scale
Statistical Methods for Data Science
Data Science Capstone Project 1
Data Science Capstone Project 2
Data Science Capstone Project 2B
Machine Learning

Part B1
at most 4 units from

Course Title
Introduction to Software Engineering
Database Principles
Advanced Database Systems
Mathematics for Data Science 1
Mathematics for Data Science 2
Applied Probability & Statistics

Part B2
at least 4 units from

Course Title
Data Mining
Advanced Techniques for High Dimensional Data
Information Retrieval and Web Search
Social Media Analytics
Numerical Linear Algebra and Optimisation
Advanced Topics in Operations Research
Operations Research & Mathematical Planning
Statistical Learning
Part C – Electives
Course Title
Concepts in Bioinformatics
Introduction to Proteins and Nucleic Acids
Advanced Bioinformatics
Advanced Genome Informatics
Pattern Recognition and Analysis
Advanced Algorithms & Data Structures
Algorithms & Data Structures
Artificial Intelligence
Numerical Methods in Computational Science
High-Performance Computing
Advanced Software Engineering
Design Thinking
Elements of Econometrics
Applied Econometrics for Macroeconomics and Finance
Financial Econometrics
Portfolio Management
Financial Mathematics
Computation in Financial Mathematics
Financial Calculus
Fundamentals of Marketing
Consumer & Buyer Behaviour
Market & Consumer Research
Introduction to Epidemiology
Mathematical Statistics
Probability Models & Stochastic Processes I
Statistical Analysis of Genetic Data
Advanced Statistics II
Advanced Probability & Stochastic Processes I
Advanced Probability & Stochastic Processes II
Longitudinal & Correlated Data
Admission Requirements

Degree equivalent to an Australian bachelor degree in Mathematics or Statistics or Computing or related discipline, with significant studies in mathematics, statistics and computing and a GPA of at least 5.0 on a 7 point scale.

Related disciplines include but are not limited to Information Technology, Computer Science, Statistics, Mathematics, Engineering, Physics, Actuarial Studies.

English Proficiency

  • IELTS overall 6.5; reading 6; writing 6; speaking 6; listening 6. For other English Language Proficiency Tests and Scores approved for UQ
  • TOEFL IBT – Overall 87, listening 19, reading 19, writing 21 and speaking 19.
  • TOEFL PB – Overall 570, listening 54, reading 54, writing 59/5.
  • Pearsons – Overall Score of 64 and 60 in all sub bands.
  • BEP – A minimum overall grade of 4 plus a minimum grade of C in all macro skills.
  • CES – Overall 176 and 169 in all sub bands.
  • OET is not accepted.
Dates & Fees

For more information on Application Dates, click here.

For more information on Fee, Scholarships and Finance matters, click here.

Contact Details

The University of Queensland
Brisbane QLD 4072

Tel: +61 7 3365 1111