Outline
Outline
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.
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
Careers
- Computer scientist
- Data analyst
- Business consultant
- Operations consultant.
Industries
- 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.
