Program Overview

The Master of Predictive Analytics addresses the growing demand for data scientists who have the right blend of technical and analytical skills to meet the challenge of big data analytics. It is currently the only master degree course in predictive analytics in Australia.

It is a multidisciplinary degree, in which you can choose from four majors to learn about specific application domains. It introduces advanced skills in data management, mining and visualisation, decision methods and predictive analytics, with a focus on their applications to different disciplines, such as engineering, networking, business and finance.

You will have opportunities to work on industry-sponsored projects, and participate in Curtin partnerships through Innovation Central Perth and the Curtin Institute for Data Science.

Upon completion of this course, you will be well placed to handle the ‘big data’ issues of the future, understand how to overlay historical and prediction data with production, financial and other data and correlate probability assessments to make better informed decisions.

Major: Data Science
The Data Science Major consolidates data science and predictive analytics skills through core machine learning and project units along with a range of optional units. Available options extend knowledge in artificial intelligence, statistics, networking and internet of things, cloud computing, security and/or industrial automation. Graduates may find employment in data analytics across a wide range of fields, particularly as an enhancement to their current academic qualifications and experience.

What you'll learn

• Apply advanced algorithms and statistical theory in the exploration, analysis and presentation of data.
• Provide innovative and creative solutions utilising data science knowledge and analytical methods.
• Communicate the implementation and outcomes of data collection, processing and presentation to both expert and non-technical audiences.
• Apply and devise new approaches to data science - potentially addressing global problems through analysis and simulation; endeavour to comply with standards and guidelines relevant to data science and to the application domain.
• Develop solutions and analyses that respect confidentiality, ethics, sustainability and maintain social responsibility.
• Demonstrate initiative and leadership when working independently and collaboratively using problem solving and decision-making skills.