Status: Planned

Overview

This track introduces the core concepts behind Physical AI: how sensors perceive the world, how actuators change it, and where machine learning fits in between.

Units

  1. What is Physical AI? History and landscape
  2. Sensors: types, interfaces, and signal conditioning
  3. Actuators: servos, motors, solenoids
  4. Microcontrollers vs. microprocessors for AI workloads
  5. Data collection and labeling for physical systems
  6. Classical ML on constrained hardware
  7. Introduction to TinyML
  8. End-to-end project: gesture-controlled LED matrix