Masters (Coursework)
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 programYou 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 onlyThe following are additional admission pathways for the Biomedical Data Science major beyond the ones listed above for all majors.
1.5 year programYou 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 programYou 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.
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 programYou 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 onlyThe following are additional admission pathways for the Biomedical Data Science major beyond the ones listed above for all majors.
1.5 year programYou 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 programYou must have successful completed LV41 Bachelor of Biomedical Science at QUT.
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 ScienceBiology 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 ScienceThe 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 45000 trips; 456000 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 ScienceIn 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.
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 option with the IN26 Graduate Certificate in Data Analytics upon completion of the required units.
To meet the course requirements for the Master of Data Analytics you must complete 192 credit points of course units consisting of:
Study Areas:
Choose your major in the following specialisation areas -
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To meet the course requirements for the Master of Data Analytics you must complete 192 credit points of course units consisting of:
Study Areas:
Choose your major in the following specialisation areas -
P