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