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: Resource Operations Analytics
The Resource Operations Analytics major involves using data analytics and disruptive technologies in the resource (oil and gas and mining) industries, how we can use predictive analytics to forecast operational engineering problems that may arise, and how best to manage them. It introduces the fundamentals of the industry, and how automation developments are linked with remote control and the decision-making processes within the future automated engineering environment.

What you'll learn

• Evaluate and apply relevant processing algorithms to data from a range of sources to solve or predict an operational problem prior to or during an occurrence.
• Develop creative solutions utilising disruptive technologies, discipline knowledge and analytical methods to forecast and manage operational resource operations engineering problems.
• Communicate the instrumentation, collection and processing of resource operations data and present outcomes and results to both expert and non-technical audiences.
• Develop improved processes and optimisation to increase yield from activities in the resources industry and help to reduce negative impacts on the environment; understand and apply established knowledge, principles, and professional practices.
• Develop solutions and analyses that respect ethics, sustainability and maintain social responsibility.
• Demonstrate initiative and leadership when working independently and collaboratively using problem solving and decision-making skills.