Master of Predictive Analytics

• CRICOS code: 092977C
• Duration: 2 years
• Course code: MC-PREDAN
• Study mode: Full-time
• Intake: February
• Location: Perth
• Indicative first-year fee: AUD$31,900

Course description

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 three streams:

Resource Operations 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

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

Asset Management and Productivity

This stream aims to develop managers who can analyse, interpret and use data relating to the assets and operations of an organisation. You will develop the skills necessary to enhance business effectiveness and provide leadership in productivity improvement and asset-utilisation. The stream focuses on the role that disruptive technologies play and the implications for strategic and operational management and leadership.

Admission criteria

• Recognised bachelor degree.
• Meet Curtin’s English proficiency requirements.

The future of predictive analytics

Experts in predictive analytics are well placed to handle the big data issues of the future. They understand how to overlay historical and prediction data with supply chain financial data, and can correlate probability assessments for better-informed decisions.

Industries

• Analytics and social media
• Corporate business
• Resource operations

For more information visit curtin.edu/mpredan