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: Internet of Things
The explosion of embedded and connected smart devices, systems and technologies in our lives has created an opportunity to connect every ‘thing’ to the Internet. The resultant data collection and connectivity generates huge amounts of data which needs to be analysed and, potentially, responded to in real-time. This is disrupting and transforming every industry around the world.
The Internet of Things Major combines the fundamentals of Predictive Analytics with IoT essentials - revealing the underlying principles and architecture of its networks, devices, programming, data, and security.

What you'll learn

• Combine communications and computing principles to create an environment to generate data for processing, presentation and analysis.
• Develop creative and innovative solutions utilising discipline knowledge and analytical methods to address challenges in Internet of Things applications.
• Present results and communicate the implementation and use of networks, sensors, data collection and processing to both expert and non-technical audiences.
• Be aware and cautious of the positive and negative potential of Things being connected and accessible globally; understand and apply established knowledge, principles, and professional practices.
• 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.