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Predictive Analytics

Master by coursework

Learn how to correlate probability assessments, handle the big data issues of the future and make informed decisions in your business or industry.

See full course structure
  • Qualification
    Master of Predictive Analytics
  • Duration
    2 years full-time
  • Credit
  • Location
    Curtin Perth
See full course structure

Select your preferred campus:


Semester 2

On campus


Semester 1

On campus

Semester 2

On campus


Semester 1

On campus

Semester 2

On campus

See full course structure


If COVID-19 restrictions apply, we may need to make changes to units and/or delivery modes.

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Broad career options

Choose from four majors to learn about specific applications of predictive analytics.

Top 1 %

Curtin is ranked in the top one per cent of universities worldwide.

Academic Ranking of World Universities 2022.

Get the Curtin edge

Access to leadership programs, specialist facilities and industry placements give you a competitive edge in the job market.

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 Computation.

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.

Resource Operations Analytics

The Resource Operations Analytics major is for petroleum and mining engineers. It gives you the ability to analyse, interpret and utilise complex data analytics relating to resource assets and operations. This major will improve your operational business decision-making, resulting in maximised asset productivity and enhanced business growth.

This major was the first course in Australia to apply data analytics and big data concepts in practice to optimise operational engineering.

Finance and Investment Analytics

The Finance and Investment Analytics major embeds economic and financial econometric analysis within the data and predictive analytic framework. It aims to help you become a data and predictive analytics expert with a working knowledge in economic, finance and business data.

You will learn to apply your skillset to different business situations, and help inform finance and investment forecasts.

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 draws on the fundamentals of Predictive Analytics to teach you the underlying principles and architecture of the Internet of Things, its networks, devices, programming, data and security.

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. These units will extend your knowledge in many areas including artificial intelligence, statistics, programming, security and automation.

This major is applicable to employment in data analytics across a wide range of fields.

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

  • You can tailor your degree to suit your career field.
  • You’ll gain advanced knowledge and undertake professional practice.
  • You’ll work on cutting-edge projects in the space of innovation and commercialisation, drawing on sophisticated research methods and techniques.
  • You’ll develop an excellent understanding of the science and application of predictive analytics, and how to improve and develop prediction software.

Career information


  • Computer scientist
  • Data analyst
  • Business consultant
  • Operations consultant.


  • Big Data
  • Finance
  • Resources engineering.

What you'll learn

  • obtain, 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; use research to apply an understanding of the theoretical basis of data analytics to produce a qualified interpretation of the data.
  • find innovative approaches to improving operations through the combination, generation and analysis of dataanalyse problems in a logical, rational and critical way; identify alternative methods of solving issues and select optimal solutions that provide the best outcomes for both industry and the community.
  • communicate effectively with a wide range of people from different discipline areas, professional positions and countries; communicate data analysis findings in a variety of ways via written, verbal or electronic communications; evaluate and utilise appropriate technology for data analysis and prediction development; appreciate the need for, and develop, a lifelong learning skills strategy in relation to enhanced personal and company performance.
  • recognise the global nature of predictive analytics in industry and apply global standard practices and skills for acceptable prediction outcomes regardless of discipline or geographical location.
  • practise appropriate industry data collection methodologies; work and apply discipline knowledge within the given social or industrial framework; with consideration of and respect for cultural diversity, indigenous perspectives and individual human rights.
  • apply lessons learnt in a professional manner in all areas of prediction design, demonstrating leadership and ethical behaviour at all times.

Admission criteria

A recognised bachelor degree.

Curtin requires all applicants to demonstrate proficiency in English. Specific English requirements for this course are outlined in the IELTS table below.

IELTS Academic (International English Language Testing System)
Writing 6.0
Speaking 6.0
Reading 6.0
Listening 6.0
Overall band score 6.0

You may demonstrate English proficiency using the following tests and qualifications.

Advanced standing

At Curtin, we understand that everyone’s study journey has been different.

You may have already studied some of the units (subjects) listed in your Curtin course, or you may have work experience that matches the degree requirements.

If this applies to you, you can apply for credit for recognised learning (CRL), which means your previous study is recognised and matched against a similar unit in your intended Curtin course.

A successful CRL application exempts you from having to complete certain units within your course and means you could finish your degree in a shorter amount of time.

CRL is also known as recognition of prior learning, advanced standing and credit transfer.

Use the CRL search to find out how much CRL you qualify for, or contact us at:

Webform: Submit here

Curtin Connect: 1300 222 888

CRL search

Fees & charges

Domestic fee paying postgraduate

Fee year: 2023

Student type Cost
Domestic $29,489*

Fees are indicative only.

* Based on a first-year full-time study load of 200 credits. The total cost will depend on your course options (i.e. units selected and time taken to complete).


For start dates, please view the academic calendar.

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Semester 2
  • On campus


Semester 1
  • On campus
Semester 2
  • On campus


Semester 1
  • On campus
Semester 2
  • On campus

All endeavours are made to ensure location information for courses is up to date but please note they are subject to change.

The University reserves the right to withdraw any unit of study or program which it offers, to impose limitations on enrolment in any unit or program, and/or to vary arrangements for any program.

How to apply

Please review information on how to apply for the campus of your choice

Please note that each campus has different application deadlines. Please view our application deadlines page for further information.

Apply now

Help is at hand

See our frequently asked questions or get in touch with us below.

Opening hours:
Mon to Fri: 8.30am – 4.30pm, except Tues: 9.30am – 4.30pm (AWST). Closed public holidays.
  • Curtin course code: MC-PREDAN
  • CRICOS code: 092977C
  • Last updated on: 27/09/2022