Master of Data Science

This course provides students with the opportunity to engage in a semester-long work-orientated project or a work-integrated experience. This provides an excellent springboard for employment following this degree. Career pathways available to data science graduates include data scientist, data analyst, machine learning scientist, statistician, informatician, computational scientist. Graduates of this course will also have the option to pursue further study at the PhD level.

Possible future job titles

Data Scientist, Data Analyst, Informatician, Computational Scientist

Higher education

Academic admission requirements (Band 6) may be satisfied through completion of one of the following:

• Bachelor degree; or
• Equivalent prior learning including at least five years relevant professional experience.

English Proficiency Requirements

English competency requirements may be satisfied through completion of one of the following:

• IELTS Academic Overall band minimum score of 6.5 (no individual band less than 6.0);
• Bachelor degree from a country specified on the English Proficiency Bands page;
• Successfully completed 0.375 EFTSL of study at postgraduate level or higher at an Australian higher education provider (or equivalent);
• Where accepted, equivalent prior learning, including at least five years relevant professional experience; or
• Other tests, courses or programs defined on the English Proficiency Bands page.

Practicum placement

Work Experience requirement

In the final semester of the course, students will complete a project involving integrated learning with a company, agency, or university academic in their discipline area.

Attendance requirements

Students will be expected to participate in a minimum of 456 hours working with an organisation on a project and produce a report on activities.

Clearances and/or Risk Management Protocols Required

Each project will have an agreement for student placement. Each workplace will be inspected, and the appropriate forms completed indicating it is a safe work environment for students. Every student will be required to complete a risk assessment and management plan as part of this placement.

If you have completed units of study at University, or have relevant professional experience, you may be eligible for Credit and Recognition of Prior Learning (CRPL).

To assess your eligibility for credit, we first need you to apply for and accept an offer in your course of interest with us. You can then submit an Application for Credit and Recognition of Prior Learning via your Student Portal. 

Data Science is an inter-disciplinary field, drawing on mathematics, statistics, and computer science, that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.

This course provides the necessary foundations in the disciplines of mathematics, statistics and computer science, and develops student knowledge and skills in some of the key tools and techniques relevant to data science. It also pays specific attention to ethical issues surrounding the manner in which data is gathered, stored and analysed/utilised.

Data Science is a significant area of growth and potential employment in Australia and the Asia-Pacific region.