Predictive analytics is the study of data to predict and subsequently optimise management decisions.

Predictive analytics uses techniques from data mining, statistics, modelling, machine learning and artificial intelligence to analyse data and make predictions about the future. It can be applied to fields such as resource operations engineering, asset management and productivity, finance, investment, actuarial science and health economics. 

The importance of predictive analytics is considerable in areas where there are new disruptive technologies. 

This course addresses the growing demand for data analysts and scientists that have the right blend of technical and analytical skills to meet big data analytics challenges. 

It emphasises the integration of technical and business skills. You will learn advanced skills in data management, data mining, decision methods, predictive analytics and visualisation, focusing on their applications to disciplines such as engineering, management, business and finance. 

You will also have opportunities to work on projects for various industries and organisations, or on analytical problems through industry sponsored projects, Innovation Central Perth, the Curtin Institute for Computation and others. 

You can specialise in one of two streams:

Resource Operations Engineering (Science and Engineering)

This stream aims to develop petroleum and mining engineers who can analyse, interpret and utilise complex data analytics relating to resource assets and operations. This will help improve their operational business decision-making, resulting in maximised asset productivity and business growth.

This is the first course in Australia to apply data analytics and big data concepts to optimise operational engineering decisions. 

Finance and Investment Analytics (Business and Law)

This stream embeds economic and financial econometric analysis within the data and predictive analytic framework. You will gain working knowledge in economic, finance and business data, enabling you to apply your analytical skills in a business context. 

Why study

• Data analytics is used to analyse data in order to draw conclusions - whereas predictive analytics is a newly emerging field that allows us to utilise this data in order to predict future outcomes, allowing companies to make better informed decisions and execute efficient strategies on disruptive technologies.
• Predictive analytics can be applied to many fields of interest, from resource operations engineering, asset management and productivity, and finance and investment, to actuarial science and health economics.

How this course will make you industry ready

The Master of Predictive Analytics (coursework) prepares students to apply advanced knowledge for professional practice, scholarship and further learning corresponding to:

• AQF level 9 qualifications
• 2-year structure of the Master Degree contains a range of discipline streams for students to choose from
• projects incorporating the use of research methods and techniques will be undertaken to demonstrate advanced knowledge and professional skills at the postgraduate level. 

This course will help you become a:

• data analyst
• operation and business consultant in resource engineering/asset management/finance.

The course will develop:

• Resource Operations Engineers with a strong knowledge of data analytics
• Scientists with the ability to improve and develop new prediction software
• Business graduates with an excellent understanding of the science and application of predictive analytics
• Finance graduates with an ability to apply predictive analytics to finance and investment forecasting decision making processes.

In addition, these graduates will be well placed to handle the ‘big data’ issues of the future, understand how to overlay historical and prediction data with supply chain financial and other business data and correlate probability assessments for better informed decisions.