University of New England
Master of Data Science
- Delivery: Online
- Study Level: Postgraduate
- Duration: 24 months
- Course Type: Master's
Gain the skills to confidently solve complex challenges in science, health, business and beyond.
Course overview
The Master of Data Science is designed for graduates from all disciplines to complement their existing skills with a solid background in statistics and computer science. It prepares them for advanced subjects in these areas along with discipline-specific data science units. The degree provides access to a backbone of statistics and computer science units provided within the course.
CSP Subsidised Fees Available
This program has a limited quota of Commonwealth Supported Places (CSP). The indicative CSP price is calculated based on first year fees for EFT. The actual fee may vary if there are choices in electives or majors.
Key facts
February, 2026
June, 2026
October, 2026
What you will study
To qualify for the award a candidate admitted under Rule (a) or Rule (d) must pass units to the value of 96 credit points including not more than 24 credit points at 100-level, not more than 12 credit points at 200/300-level and at least 36 credit points at 500-level.
To qualify for the award a candidate admitted under Rule (b) or Rule (c) must pass units to the value of 96 credit points including at least 36 credit points at 500-level.
Core units
Complete the following units:
Note: When a unit with the same title is offered at multiple levels you can only complete ONE unit (eg. STAT210 or STAT410).
Note: Students are encouraged (but not required) to complete STAT410 before undertaking STAT430.
- Mathematics for Machine Learning and Artificial Intelligence
- Introduction to Programming and the UNIX Environment
- Fundamentals of Cybersecurity and Privacy
- Database Management Systems
- Software Project Management
- Artificial Intelligence
- Management Information Systems
- Algorithms in Machine Learning
- Statistical Modelling and Experimental Design (STAT210 or STAT410)
- Statistical Learning
Additional core
Complete one of the following units:
- Introduction to Statistical Modelling
- Data Science Studio one
Research/capstone experience
Complete either the Major Thesis Project or the Research Project:
Major thesis project
Complete the following units:
- Information Technology Project
- Computing Science/IT Thesis (24 credit points)
Research project
Complete the following units and complete 18 credit points from the listed units:
- Information Technology Project
- Special Topics in Science A
Listed units
Complete zero or 18 credit points with at least 12 credit points at 500-level from the following units:
- Computational Mathematics
- Data Structures and Algorithms
- Operating Systems
- Programming Paradigms
- Web Programming
- Parallel and Distributed Computing
- Computer Networks and Network Security
- Deep Learning
- Reinforcement Learning
- Advanced Web Programming
- User Experience and Interaction Design
- Information Privacy
- Introductory Econometrics
- Econometric Analysis of Financial Markets
- Genomic Analysis and Bioinformatics
- Information and Knowledge Management in Healthcare
- Precision Agriculture
- Advanced Statistical Modelling
- Introduction to Scientific Programming
- Statistical Learning
- Frequentist and Bayesian Statistical Inference
Entry requirements
This course is offered under three admission rules:
Rule A: You have completed a Bachelor qualification (AQF Level 7 or overseas equivalent) in any discipline.
If admitted on this basis, you will be eligible for admission under Rule A.
Rule B: You have completed a Bachelor qualification (AQF Level 7) in a relevant discipline.
If admitted on this basis, you will be eligible for admission under Rule B.
Rule C: You have completed a Graduate Certificate, Graduate Diploma or Bachelor with Honours (AQF Level 8 or overseas equivalent) in a relevant discipline.
If admitted on this basis, you will be eligible for admission under Rule C.
Relevant disciplines include, but are not limited to, the following:
- Computer Science
- Data Science
- Information Systems
- Information Technology
- Mathematics
- Software Engineering
- Statistics
English Language Requirements
- When applying, you may be required to show how you satisfy the English Language Requirements for this course.
Recognition of Prior Learning
Advanced Standing is credit or recognition of your previous study, work and/or life experience. This can reduce the cost and length of your studies.
Course Entry Advanced Standing
Some entry rules come with Advanced Standing or Articulation Programs that are assessed automatically without the need for you to fill in an additional application. Simply apply for your course and we’ll look after the rest.
- If you are admitted under Rule B, you will be granted 24 credit points of Block Advanced Standing.
- If you are admitted under Rule C, you will be granted 48 credit points of Block Advanced Standing. You cannot apply for further Advanced Standing.
Individual Unit Advanced Standing
If you are admitted into this course and believe you have already completed the equivalent of one or more of the units in your study within the last ten years, you can apply for Individual Unit Advanced Standing.
- If you are admitted under Rules A or D, you can apply for up to 48 credit points of Advanced Standing. This may include up to six credit points of Advanced Standing based on relevant professional experience.
- If you are admitted under Rule B, you can apply for up a further 24 credit points of Advanced Standing. This may include up to six credit points of Advanced Standing based on relevant professional experience.
Please note: Advanced Standing cannot be granted for the following units:
- Information Technology Project
- Special Topics in Science A
Outcomes
Learning outcomes
- Understand the key tools, methods and theories used in data science to a level of depth and sophistication consistent with advanced professional practice;
- Synthesise information from data and analyse the lifecycle of data within an organisation;
- Apply problem solving skills and advanced knowledge to implement data analysis solutions for real-world problems;
- Communicate effectively with expert and non-expert audiences to understand issues and gather requirements for the development of data analysis strategies and related systems within an organisation;
- Integrate theories and methods related to data science, statistics and software development by planning and executing a research-grounded industry project;
- Evaluate information from a range of sources, such as peer-reviewed literature and technical documentation, to assess current developments in the area of data science; and
- Demonstrate a sophisticated awareness of the ethical and legal issues that relate to the practice of data science.
Career outcomes
You will be equipped with the skills and knowledge needed to advance your career in positions such as:
- Data Scientist
- Business Intelligence Analyst
- Data Engineer or Architect
- Data Strategist
- Healthcare Data Manager
- Bioinformatics Analyst.
Fees and CSP
Estimated first-year fee in 2026: $8,341 (Commonwealth Supported Place)
Estimated first-year fee in 2026: $24,384 (domestic full-fee paying place)
Estimated amenities fee per year if studying full-time: $373
The costs will depend on the units you choose to study, as the cost of individual units varies. “Estimated fees” are provided as a guide only based on a typical enrolment of students undertaking a study load of 48 credit points in the first year of this course. For courses that require fewer than 48 credit points, the fees indicated are based on the total credit points needed for the completion of that course.
Student fees may vary in accordance with:
- The number of units studied per term.
- The choice of major or specialisation.
- Choice of units.
- Credit from previous study or work experience.
- Eligibility for government-funded loans.
Commonwealth Supported Places
The Australian Government allocates a certain number of CSPs to the universities each year, which are then distributed to students based on merit.
If you're a Commonwealth Supported Student (CSS), you'll only need to pay a portion of your tuition fees. This is known as the student contribution amount – the balance once the government subsidy is applied. This means your costs are much lower.
Limited CSP spaces are offered to students enrolled in selected postgraduate courses.
Your student contribution amount is:
- Calculated per unit you're enrolled in.
- Dependent on the study areas they relate to.
- Reviewed and adjusted each year.
Student fees shown are subject to change. Contact the university directly to confirm.
FEE-HELP loans are available to assist eligible full-fee paying domestic students.
HECS-HELP loans are available to CSP students to pay the student contribution amount.