This course contains the use of artificial intelligence. Physical AI is the next major evolution of artificial intelligence: AI that can perceive the physical world, reason about space and objects, make decisions, and act through robots and autonomous machines. This course provides a structured foundation in Physical AI, robotics, embodied intelligence, Vision-Language-Action models, world models, spatial intelligence, Edge AI, robot learning, simulation, digital twins and autonomous systems. Unlike Generative AI, which primarily creates content, or Agentic AI, which plans and acts through digital tools and software environments, Physical AI connects intelligence with the physical world. It brings together perception, reasoning, planning, learning and control so that machines can interact with real environments.
The course is designed for learners who want to understand the technologies, learning methods, business applications and governance challenges behind the emerging Physical AI ecosystem.
A useful way to understand Physical AI is: Sense -> Understand -> Reason -> Plan -> Act -> Learn
Machines first perceive the environment through sensors and visual inputs. They then build an understanding of objects, space and context. AI models reason about the situation and determine an appropriate action. Planning and control systems convert that decision into physical movement. Finally, data from the outcome can contribute to future learning and improvement. This complete loop is what makes Physical AI fundamentally different from purely digital AI systems.
