Highlights

  • Be at the cutting edge of a booming new field of expertise that can be applied across industries.
  • Translate data into insight and intelligence to be able to drive change and make key decisions.
  • Solve domain-relevant problems by synthesising knowledge from mathematics, statistics, computer science, information systems and business process management.
  • Learn from expert academics and leading researchers who apply data science and data analytics to a range of real-world challenges, and who have world-wide industry connections.

Highlights

  • Be at the cutting edge of a booming new field of expertise that can be applied across industries.
  • Translate data into insight and intelligence to be able to drive change and make key decisions.
  • Solve domain-relevant problems by synthesising knowledge from mathematics, statistics, computer science, information systems and business process management.
  • Learn from expert academics and leading researchers who apply data science and data analytics to a range of real-world challenges, and who have world-wide industry connections.

Why choose this course?

Be future-focused and stay ahead of the curve. Drive real change and impact key decisions by learning how to make sense of the volume, variety, and velocity of data we collect as a society.

Our academics are world leaders in research and have strong industry ties that ensures the relevance of teaching material and high-quality learning experiences for students.

Real-world learning

This course is designed to specifically meet industry needs. We’ve brought together expertise in statistics, computer science, and business process management disciplines to deliver real-world learning opportunities.

You'll:

  • build significant project-based experience that allows you to constructively apply your analytical skills to complex problem domains
  • experience applying high-order thinking strategies within data-rich contexts through the synthesis of multiple sources of information
  • apply specialist abstraction and synthesis techniques to solve complex data analytics problems that are inspired by real-world scenarios.

Explore this course

What to expect

This course will prepare you for a future-focused career in the fast-paced, ever-changing world of data analytics. With a collaborative curriculum across disciplines you’ll not only learn theories and methods, but you’ll apply that knowledge to predict, forecast, visualise and make decisions in a range of applied areas.

You will study specialist units in advanced statistical data analysis, data mining techniques and applications, data manipulation, analytics for information professionals and advanced stochastic modelling.

You can choose from three majors, plus a "No Major" option for this course:

Biomedical Data Science
Biology and medicine are becoming increasingly data-intensive in research and clinical practice. From new sequencing technologies to medical imaging  and electronic health records, to wearable devices recording heart rate, it has never been easier or cheaper to generate biomedical data.

Yet these datasets may be large and complex, and the observations noisy. This interdisciplinary major provides the skills you need to 'wrangle' and analyse biomedical data. You will learn statistical and machine learning methods, and use them to identify relationships and gain insight into function and disease states, while gaining some understanding of their limitations and the complexity of the problems which arise. 

Computational Data Science
The world is awash in data and it's growing at a mammoth pace. Over 2.5 million trillion byes of data are generated every day. In every minute Uber has 45,000 trips; 456,000 tweets are sent; and 3.6 million Google searches occur. NASA alone generates 121 terabytes of data every single day.

This major will equip you with the knowledge and skills to bring order to the chaos on terabytes of data and extract meaning. You'll be confident in searching for hidden models, training intelligent systems, creating visualizations, identifying patterns and trends, and discovering solutions and opportunities. You'll undertake data analysis and research across domains, with the focus on the development and application of computational methods which scale as the number of records increases. 

Statistical Data Science
In this digital and data-rich era the demand for statistical experts is high, yet the pool of such graduates is small. The recent growth of data science has increased the awareness of the importance of statistics, with the analysis of data and interpretation of the results firmly embedded within this newly recognised field.

This major provides advanced training in statistics, together with complementary skills in programming and data extraction and mining. This combination gives you the background and experience to gather and evaluate data-based evidence to support informed decision-making, and to advise on the robustness and the uncertainty of the conclusions drawn.

For more information about the course structure and the units for each major, please refer to the "Details and Units" tab.

Careers and outcomes

Careers and outcomes

When you graduate, you’ll be able to apply different approaches, techniques and tools to data in different industry contexts to solve complex problems.

You'll have the skills necessary to transform data into knowledge for any industry, including banking and finance, media and communications, health, education, information technology, engineering, agriculture and mining.

Early exit

Early exit option with the IN26 Graduate Certificate in Data Analytics upon completion of the required units.

Possible careers

  • Data Analyst
  • Data Analytics Specialist
  • Data Systems Developer
  • Data-Driven Decision Maker

Details and units

To meet the course requirements for the Master of Data Analytics, you must complete 192 credit points of course units, consisting of:

  • 48 credit points of core units
  • 96 credit points of discpline units from your selected Major, or a range of units from across the majors if you choose not to nominate a major.
  • 48 credit points of data analytics related elective units selected from an approved list of units, which is drawn from units offered in each of the majors.

Study Areas:
Choose your major in the following specialisation areas -

  • Biomedical Data Science;
  • Computational Data Science;
  • Statistical Data Science; or
  • No Major option

Students in the 1.5 year program

Please note: study plans are determined based on prior qualifications. The placement of the 48 credit point reduction across the study plan may vary between students. Clarification can be sought from the Course Coordinators once admitted.

To meet the course requirements for the Master of Data Analytics, you must complete 192 credit points of course units, consisting of:

  • 48 credit points of core units
  • 96 credit points of discpline units from your selected Major, or a range of units from across the majors if you choose not to nominate a major.
  • 48 credit points of data analytics related elective units selected from an approved list of units, which is drawn from units offered in each of the majors.

Study Areas:
Choose your major in the following specialisation areas -

  • Biomedical Data Science;
  • Computational Data Science;
  • Statistical Data Science; or
  • No Major option

Students in the 1.5 year program

Please note: study plans are determined based on prior qualifications. The placement of the 48 credit point reduction across the study plan may vary between students. Clarification can be sought from the Course Coordinators once admitted.

Requirements

Course code
IN27
CRICOS code
098601J
Delivery
  • Gardens Point
Delivery
  • Gardens Point
Duration
1 - 2 years full-time
2 - 4 years part-time
Duration
2 years full-time
Entry
February and July
Entry
February and July

2 year program

A recognised bachelor degree (or higher qualification) in any discipline with a minimum grade point average (GPA) of 4.00 (on QUT's 7 point scale).
 

1.5 year program

A recognised bachelor degree (or higher qualification) in information technology or mathematics with a minimum grade point average (GPA) score of 4.00 (on QUT's 7 point scale).
 

1 year program

Minimum academic requirements

Academic entry requirements

1.5 year program

You must have a completed recognised bachelor degree in information technology or mathematics (or related field), with a minimum grade point average of 4.00 (on QUT's 7 point scale).

2 year program

You must have a completed recognised bachelor degree in any discipline with a minimum grade point average of 4.0 (on QUT's 7 point scale).

Minimum English language requirements

Select the country where you completed your studies to see a guide on meeting QUT’s English language requirements.

Your scores and prior qualifications in English-speaking countries are considered. Approved English-speaking countries are Australia, Canada, England, Ireland, New Zealand, Scotland, South Africa, United States of America and Wales.

If your country or qualification is not listed, you can still apply for this course and we will assess your eligibility.

We accept English language proficiency scores from the following tests.

English Test Overall Listening Reading Writing Speaking
Pearson PTE (Academic)
Test must be taken no more than 2 years prior to the QUT course commencement date.
58 50 50 50 50
Cambridge English Score
Test must be taken no more than 2 years prior to the QUT course commencement. You must provide your Candidate ID and Candidate Secret Number, these are printed on your Cambridge English Confirmation of Entry.
176 169 169 169 169
IELTS Academic
Test must be taken no more than 2 years prior to the QUT course commencement date.
6.5 6 6 6 6
TOEFL iBT
Test must be taken no more than 2 years prior to the QUT course commencement date.
79 16 16 21 18

Don't have the English language score you need? We can help!

We offer English language programs to improve your English and help you gain entry to this course.

When you apply for this course, we will recommend which English course you should enrol in.

Haven't completed an English language test? We can help!

If you have not completed an English language test, you can sit the IELTS test at our IELTS test centre

Fees

Your actual fees may vary depending on which units you choose. We review fees annually, and they may be subject to increases.

2021 fees

2021: $24,700 per year full-time (96 credit points)

2021 fees

2021: $34,100 per year full-time (96 credit points)

Student services and amenities fees

You may need to pay student services and amenities (SA) fees as part of your course costs.

Find out more about postgraduate course fees

FEE-HELP: loans to help you pay your course fees

You may not have to pay anything upfront if you're eligible for a FEE-HELP loan.

Find out more about government loans

Scholarships

You can apply for scholarships to help you with study and living costs.

Browse all scholarships