Sally's study journey
'The course was structured well so that students were gradually introduced to new concepts. Also, the teaching team at QUT is extremely supportive, there were no unanswered questions and students were encouraged to ask lots of questions. The supportive environment made me feel comfortable, and I was able to learn concepts of statistics, and how to code.'
Respond to industry demands
'I decided to study a Master of Data Analytics because as a software computer engineer, I discovered a growing industry demand for data science and analytics skills. I chose QUT because of its solid relationships with industry. The assignments and units are designed to prepare you for big challenges and tasks in the industry.'
Tangible skills for the workforce
'The Master of Data Analytics has helped me develop statistical, computational and research skills to better inform research methods and data structuring and improve business and governance processes. I have had the opportunity to analyse real data sets from sources such as Queensland hospitals, international COVID-19 surveys and waste management in New South Wales, providing tangible skills I can take to the workforce.'
Tangible skills for the workforce
'The Master of Data Analytics has helped me develop statistical, computational and research skills to better inform research methods and data structuring and improve business and governance processes. I have had the opportunity to analyse real data sets from sources such as Queensland hospitals, international COVID-19 surveys and waste management in New South Wales, providing tangible skills I can take to the workforce.'
Sally's study journey
'The course was structured well so that students were gradually introduced to new concepts. Also, the teaching team at QUT is extremely supportive, there were no unanswered questions and students were encouraged to ask lots of questions. The supportive environment made me feel comfortable, and I was able to learn concepts of statistics, and how to code.'
Respond to industry demands
'I decided to study a Master of Data Analytics because as a software computer engineer, I discovered a growing industry demand for data science and analytics skills. I chose QUT because of its solid relationships with industry. The assignments and units are designed to prepare you for big challenges and tasks in the industry.'
Highlights
- NEW: This course now offers Commonwealth Supported Places which makes it over 60% more affordable. Eligibility criteria applies.
- 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.
- QUT is Australia's top research institution for Data Mining and Analysis (Australian Research Magazine 2024).
- 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.
- QUT is Australia's top research institution for Data Mining and Analysis (Australian Research Magazine 2024).
- 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.
This course now offers Commonwealth Supported Places which makes it over 60% more affordable. Eligibility criteria applies.
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
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 bytes 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
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
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.
- Course code
- IN27
- CRICOS code
- 098601J
-
- Gardens Point
-
- Gardens Point
- 1 - 2 years full-time
- 2 - 4 years part-time
- 2 years full-time
- February and July
- February and July
Entry requirements - all majors
2 year program
You must have 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
You must have 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).
Entry requirements - Biomedical Data Science major only
The following are additional admission pathways for the Biomedical Data Science major beyond the ones listed above for all majors.
1.5 year program
You must have a recognised bachelor degree (or higher qualification) in biomedical science with a minimum grade point average (GPA) score of 4.00 (on QUT's 7 point scale).
1 year program
You must have successful completed LV41 Bachelor of Biomedical Science at QUT.
Graduates will automatically receive an offer to start within three weeks of the current semester results being released.
Minimum academic requirements
Entry requirements - all majors
2 year program
You must have a completed recognised bachelor degree (or higher qualification) in any discipline with a minimum grade point average of 4.00 (on QUT's 7 point scale).
1.5 year program
You must have a completed recognised bachelor degree (or higher qualification) in information technology or mathematics (or related field), with a minimum grade point average of 4.00 (on QUT's 7 point scale).
Entry requirements - Biomedical Data Science major only
The following are additional admission pathways for the Biomedical Data Science major beyond the ones listed above for all majors.
1.5 year program
You must have a recognised bachelor degree (or higher qualification) in biomedical science with a minimum grade point average (GPA) score of 4.00 (on QUT's 7 point scale).
1 year program
You must have successful completed LV41 Bachelor of Biomedical Science at QUT.
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, 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. Tests must be taken no more than 2 years prior to the QUT course commencement.
English Test | Overall | Listening | Reading | Writing | Speaking |
---|---|---|---|---|---|
PTE Academic/PTE Academic Online | 58 | 50 | 50 | 50 | 50 |
Cambridge English Score
You must share your results with QUT through the Candidate Results Online website. |
176 | 169 | 169 | 169 | 169 |
IELTS Academic / IELTS Online / IELTS One Skills Retake | 6.5 | 6 | 6 | 6 | 6 |
TOEFL iBT / Home / Paper | 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.
Advanced standing
If you are offered the 1.5 year program, you will receive 48 credit points (1 semester) of advanced standing. For more information please view the following advanced standing precedents:
If you have been admitted to the 1 year program you will receive a further 48 credit points of advanced standing in addition to the above.
Your actual fees may vary depending on which units you choose. We review fees annually, and they may be subject to increases.
2025 fees
2025: CSP fees available from September
2025 fees
2025: Available from July
2024 fees
2024: CSP $8,400 per year full-time (96 credit points)
2024 fees
2024: $38,100 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.
HECS-HELP: loans to help you pay for your course fees
You may not have to pay anything upfront if you're eligible for a HECS-HELP loan.
You can apply for scholarships to help you with study and living costs.
Oodgeroo Noonuccal Undergraduate & Postgraduate Scholarship
The Oodgeroo Scholarship Program promotes the pursuit of Indigenous Australian studies by supporting the education of Indigenous Australians.
- Scholarship eligibility
- Indigenous Australian
QUT Real World International Scholarship
A scholarship to cover tuition fees, with eligibility based on your prior academic achievements.
- Scholarship eligibility
- Academic performance
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