Graduate Certificate in Predictive Analytics
|Study method||Part-time or full-time|
|Duration||6 months full-time|
The big data revolution is upon us and our lifestyles will be hugely influenced by real-time customer data and predictive analytics. As companies try to understand us better and to identify potential risks and opportunities, there is a growing demand for data analysts who have the right blend of technical and analytical skills to meet the challenge.
The Graduate Certificate in Predictive Analytics gives you the opportunity to start building these skills, and take your career in the right direction. You'll learn the basics of predictive data analytics and concepts of data analysis, computing and visualisation, and find out how these concepts can be used to predict future scenarios.
When you complete the course, you may be eligible to enter the Graduate Diploma in Predictive Analytics and the Master of Predictive Analytics course.
Entry requirements for Australian and New Zealand students
You generally require a bachelor degree or equivalent credit gained for recognised learning.
You must also meet the University's English language requirement.
Fees for Australian and New Zealand students
|2017||Domestic fee paying Domestic fee-paying - A domestic fee-paying place is a place at university which is not Commonwealth supported, that is, not subsidised by the Australian Government. Domestic fee paying students will be charged tuition fees and may be eligible for FEE-HELP assistance for all or part of those tuition fees.||$13,400*|
Fees are indicative only.
* Based on a first-year full-time study load of 100 credits. The total cost will depend on your course options (i.e. units selected and time taken to complete).
Applications are assessed on an individual basis
Learn about Credit for Recognised Learning (CRL)
Predictive analytics uses techniques from data mining, statistics, modelling, machine learning, and artificial intelligence to analyse current data and make predictions about the future. It 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. The importance of predictive analytics is considerable in areas where there are new disruptive technologies.
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.
More information about Predictive Analytics