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Parts Overview

Master Physical AI and Humanoid Robotics through our structured five-part curriculum, designed to take you from fundamentals to advanced embodied intelligence

5Parts
21Chapters
32+Hours
Part 1

Foundations

Understanding the fundamentals of Physical AI and embodied intelligence

3 hours3 Chapters

Key Topics

  • Embodied AI concepts
  • Physical constraints
  • Sensor systems
  • Actuator mechanisms

Learning Outcomes

  • Understand physical AI principles
  • Design basic embodied systems

Chapters in this Part

Chapter 1Beginner

What is Physical AI?

45 min
Chapter 2Intermediate

Embodied Intelligence

60 min
Chapter 3Intermediate

Sensors, Actuators & Physical Limits

75 min
Part 2

ROS Fundamentals

Master the Robot Operating System and its core concepts

5.5 hours3 Chapters

Key Topics

  • ROS2 architecture
  • Communication patterns
  • Robot modeling
  • Coordinate frames

Learning Outcomes

  • Build ROS2 applications
  • Design robot models
  • Implement communication

Chapters in this Part

Chapter 4Intermediate

ROS2 Fundamentals

90 min
Chapter 5Intermediate

Nodes, Topics, Services & Actions

120 min
Chapter 6Advanced

URDF, Robot Description & TF Trees

105 min
Part 3

Simulation & Digital Twins

Create realistic simulations and digital twins for robotic systems

9 hours6 Chapters

Key Topics

  • Physics engines
  • 3D visualization
  • Synthetic data
  • Digital twins

Learning Outcomes

  • Create realistic simulations
  • Generate training data
  • Build digital twins

Chapters in this Part

Chapter 7Advanced

Gazebo Physics Simulation

100 min
Chapter 8Intermediate

Unity Robotics Visualization

85 min
Chapter 9Advanced

NVIDIA Isaac Synthetic Data

70 min
Chapter 10Advanced

Physics Simulations

95 min
Chapter 11Advanced

Isaac Sim Platform

110 min
Chapter 12Advanced

Digital Twin Development

90 min
Part 4

Perception & State Estimation

Implement perception systems and state estimation for autonomous robots

7 hours4 Chapters

Key Topics

  • Computer vision
  • Sensor fusion
  • SLAM algorithms
  • Path planning

Learning Outcomes

  • Implement vision systems
  • Fuse sensor data
  • Navigate autonomously

Chapters in this Part

Chapter 13Advanced

Computer Vision for Robots

115 min
Chapter 14Advanced

Sensor Fusion & State Estimation

100 min
Chapter 15Expert

SLAM, VSLAM & Navigation

130 min
Chapter 16Advanced

Path Planning Algorithms

95 min
Part 5

Embodied Intelligence

Advanced AI techniques for physical embodiment and autonomous systems

7.5 hours5 Chapters

Key Topics

  • Multimodal AI
  • Language models
  • Cognitive architectures
  • Humanoid robots
  • AI ethics

Learning Outcomes

  • Build intelligent agents
  • Implement language understanding
  • Design ethical AI

Chapters in this Part

Chapter 17Expert

Vision-Language-Action Models

85 min
Chapter 18Expert

Voice-to-Action Pipelines (Whisper)

75 min
Chapter 19Expert

Cognitive Planning with GPT

80 min
Chapter 20Expert

The Autonomous Humanoid

120 min
Chapter 21Expert

Ethical Considerations in Embodied AI

90 min

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