Resource Operations Analytics Major (M PredAnylt)

  • //applyindex.com/wp-content/uploads/2021/09/australia.png Australia
  • University/Institute Name Curtin University
  • Attendance Type On Campus (Full Time)
  • Position Duration2 years
  • Application deadlineExpired

Position Details (Master's)

The Resource Operations Analytics Major (M PredAnylt) program at Curtin University introduces the fundamentals of the industry, and how automation developments are linked with remote control and the decision-making processes within the future automated engineering environment.

The Resource Operations Analytics Major (M PredAnylt) program at Curtin University involves using data analytics and disruptive technologies in the resource (oil and gas and mining) industries, how we can use predictive analytics to forecast operational engineering problems that may arise, and how best to manage them.

What you'll learn

  • 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.
  • develop creative solutions utilising disruptive technologies, discipline knowledge and analytical methods to forecast and manage operational resource operations engineering problems.
  • communicate the instrumentation, collection and processing of resource operations data and present outcomes and results to both expert and non-technical audiences.
  • develop improved processes and optimisation to increase yield from activities in the resources industry and help to reduce negative impacts on the environment; understand and apply established knowledge, principles, and professional practices.
  • develop solutions and analyses that respect ethics, sustainability and maintain social responsibility.
  • demonstrate initiative and leadership when working independently and collaboratively using problem solving and decision-making skills.
Courses include:
  • New Product Development
  • Systems Control and Remote Operations
  • Explainable Approaches to Machine Learning
  • Natural Resources Economics
  • Supply Chain Planning and Design
  • Predictive Analytics Project
  • Natural Resources Economics

Research Areas & Fields of Study involved in the position

Position Start Date

Feb 2026