Master of Data Analytics

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.

• Master of Data Analytics - No Major option
• Biomedical Data Science Major
• Biomedical Data Science Major - Math cognate entrant
• Biomedical Data Science Major - IT cognate entrant
• Biomedical Data Science Major - Biomed cognate entrant
• Biomedical Data Science Major Unit Options
• Computational Data Science Major
• Computational Data Science Major - IT cognate entrant
• Computational Data Science Major - Math cognate entrant
• Computational Data Science Major Unit Options
• Statistical Data Science Major
• Statistical Data Science Major - IT cognate entrant
• Statistical Data Science Major - Math cognate entrant
• Statistical Data Science Major Unit Options
• Master of Data Analytics Electives Lists

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.

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