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Analytics for Digital Twins

Master data analytics for digital twins and learn to create powerful cloud-based virtual models. Transform raw data into actionable insights that drive operational excellence.

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Key Information

The Analytics for Digital Twins Micro-credential provides learners with the knowledge and skills required to store and analyse data for use in digital twin software.

A digital twin is virtual model of a physical object or system that spans its lifecycle and brings in learning and experiences from real world processes to update the digital twin model. Engineers and operators can view the digital twin to understand, in real time, how the asset or system is performing in the real world.

Analysis of the data collected from the digital twin can also support decision-making based on predictions of how the asset or system will perform in the future. Furthermore, the operational data provides insight to manufacturers to optimise the product design, improve manufacturing processes, and deliver sustainable products at a reduced cost.

This micro-credential builds upon the fundamentals taught in the Introduction to Digital Twin course while focusing on data analytics for digital twins.

This course is suited to:

  • Managers (ANZSCO ID 1351)
  • Engineers
  • Data Analysts.

The Analytics for Digital Twins Micro-credential involves a volume of learning of approximately 40 hours of student effort.

 
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Breakdown of the Course/Module

Upon completion, learners will be able to:

  • Understand types of data and database structures in the cloud
  • Understand digital thread concepts to realise a digital twin
  • Understand different data visualisation and analytics tools and use them to gain insights from the data
  • Apply data driven decision-making
  • Create a digital twin in the cloud
  • Understand the value of digital twin technology.

 

Damian Jolly

About your trainer

Damian Jolly
Trainer

With more than 25 years of experience, Damian specialises in industrial automation, process control, cloud technologies, and data analytics. As a Principal Consultant at Nukon for seven years, he led solutions for waste management, food and beverage, manufacturing, and mining clients, focusing on Industry 4.0 roadmaps and Lean Thinking to improve efficiency. Damian also co-authored the 22460VIC Industrial Networks and Communications Performance Activities course, reflecting his dedication to advancing industry knowledge and education. Having designed and project-managed solutions using AWS and Azure cloud technologies, as well as working with data platforms such as MSSQL, PostgreSQL, Databricks, Redshift, and IoT platforms such as AWS IoT, Damian brings a wealth of hands-on experience to each training session.

FAQs

Yes, learners should have completed the Introduction to Digital Twins Micro-credential or have commensurate professional experience (3 to 5 years’ relevant work experience). 

The volume of learning is approximately 40 hours of student effort.

At this time, there is no funding available for this micro-credential. Pricing information is available on this page. 

Yes, our micro-credentials can be stacked, which means that learners can make continuous progress towards a certificate or diploma qualification, completed at a pace that suits you. 

The USI is a code made up of 10 numbers and letters which is assigned to individual students and remains with the student for life. The USI is used to create a secure online record of your recognised training and qualifications awarded to you in Australia. You can access your online records by logging in onto the USI portal. Read more getting a USI here. 

With our cyber physical training, you can complete the course from anywhere, as long as you have a reliable internet connection. Many users have found having two screens to be easier. Information on how to access training platforms will be emailed to you prior to the course commencing.

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