88797- Advanced Digital Twin Mastery: Modelling, Optimization, and Implementation (Pilot)

Type of course:

Digital learning, Path

Proficiency:

Intermediate

Target:

Professionals, Students

SUMMARY

This learning path offers a comprehensive journey into advanced concepts and applications of digital twins, integrating insights from two expert-led courses: Mastering Digital Twins: Advanced Modeling, Optimization, and Control and Building Upon the Bridges: Advanced Concepts in Digital Twin Implementation.

You’ll explore critical topics such as lifecycle management, interoperability standards, cybersecurity, and emerging business models. The path delves into sophisticated methodologies like state-space modeling, parameter estimation, optimization techniques, and dynamic control systems such as Model Predictive Control (MPC). Advanced mathematical frameworks, robust estimation strategies (e.g., Kalman Filters), and optimization under uncertainty using gradient-based and meta-heuristic algorithms are central themes.

To solidify your understanding, the learning path includes a comprehensive quiz designed to test your grasp of both foundational and advanced concepts, ensuring you are well-equipped to apply digital twin strategies in real-world scenarios.

About The Author

Ioannis Astli is a Data Scientist at the CORE Innovation Centre, with a strong academic foundation holding an MSci in Computer Engineering. Driven by a deep passion for Artificial Intelligence, he consistently advocates for advancing AI knowledge and its practical applications across various domains.

Learning outcomes

Examine and test advanced modelling techniques such as state-space representation and parameter estimation to analyze and simulate dynamic systems with at least 85% accuracy in problem-solving scenarios by the end of the learning path.
Implement optimization strategies and dynamic control methods, including Model Predictive Control, to enhance system efficiency, achieving measurable improvements in simulated case studies by completion.
Demonstrate proficiency in lifecycle management, interoperability standards, and cybersecurity by successfully completing a final assessment that evaluates practical application and theoretical understanding with a minimum score of 80%.