Digital Twins

Partner: Udemy
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Description: SummaryThe concept of Digital Twins has emerged as a transformative paradigm in the design, analysis, and operation of complex physical, cyber-physical, and socio-technical systems. A Digital Twin is more than just a model—it is a living, data-driven representation of a real-world entity that enables simulation, prediction, monitoring, and control in real time. This course explores the foundational concepts of Digital Twins, their reference architectures, common design patterns, and their powerful synergy with AI agents and data science methodologies. We will examine how Digital Twins enable intelligent system behavior, decision-making, and adaptation across various domains such as smart manufacturing, healthcare, agriculture, mobility, and infrastructure.The course offers a systematic overview of how to conceptualize, design, and evaluate Digital Twins using principles from systems engineering, software architecture, and artificial intelligence. Upon completion, learners will have a deep understanding of the Digital Twin paradigm, practical design strategies, and the role of AI and data technologies in enabling high-fidelity twin systems.Key Topics· Core concepts and definitions of Digital Twins· Digital Twin reference architectures· Digital Twin design patterns· Integration of AI agents with Digital Twins· Role of data science and machine learning· Modeling and simulation in Digital Twin environments· Synchronization between physical and virtual systems· Applications across sectors (e.g., health, agriculture, energy, mobility)· Challenges in scalability, interoperability, and real-time data handlingKey Learning Objectives· Understand the fundamental principles and lifecycle of Digital Twins· Analyze and design Digital Twin reference architectures· Apply common design patterns for structuring Digital Twin systems· Integrate AI agents and data-driven intelligence in Digi
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Price: 79.99
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Source: Impact
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