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Weekly Curriculum Overview

Course Structure​

This 13-week curriculum provides a comprehensive introduction to Physical AI, progressing from fundamental concepts to advanced implementations. Each week builds upon the previous, creating a cohesive learning experience that follows the simulation-first development approach.

Weekly Breakdown​

Weeks 1-3: ROS 2 - The Robotic Nervous System​

  • Week 1: ROS 2 fundamentals, nodes, topics, and basic communication
  • Week 2: Services, actions, parameters, and advanced communication patterns
  • Week 3: ROS 2 tools, debugging, and system integration

Weeks 4-6: Simulation Environments​

  • Week 4: Gazebo simulation basics, robot models, and physics
  • Week 5: Unity integration for advanced visualization and simulation
  • Week 6: Simulation-to-reality transfer techniques and validation

Weeks 7-9: NVIDIA Isaac Platform​

  • Week 7: Isaac Sim introduction and perception systems
  • Week 8: Isaac ROS integration and hardware deployment
  • Week 9: Advanced perception and manipulation with Isaac

Weeks 10-12: Vision Language Action (VLA) Models​

  • Week 10: Introduction to VLA models and multimodal AI
  • Week 11: Training and fine-tuning VLA models for robotics
  • Week 12: Integrating VLA models with robotic systems

Week 13: Capstone Project​

  • Integration of all learned concepts
  • Autonomous humanoid robot implementation
  • Voice command processing and execution
  • Final demonstration and evaluation

Learning Objectives by Week​

Each week has specific learning objectives designed to build toward the capstone project:

  1. Technical Mastery: Students will gain proficiency in the tools and frameworks relevant to each week's focus
  2. Integration Skills: Students will learn how to connect different components into cohesive systems
  3. Problem-Solving: Students will develop skills to debug and troubleshoot complex robotic systems
  4. Simulation-to-Reality: Students will understand the principles of transferring simulation-based solutions to real-world applications

Assessment Structure​

  • Weekly Exercises: Hands-on projects that reinforce the week's concepts
  • Mid-term Project: Integration project covering the first half of the curriculum
  • Capstone Project: Comprehensive implementation of an autonomous humanoid robot
  • Peer Reviews: Students will review and provide feedback on each other's implementations

Prerequisites by Week​

  • Weeks 1-3: Basic programming knowledge (Python preferred)
  • Weeks 4-6: Understanding of ROS 2 concepts from Weeks 1-3
  • Weeks 7-9: Completion of simulation environment modules
  • Weeks 10-12: Understanding of perception systems and basic AI concepts
  • Week 13: Completion of all previous modules

Resources and Support​

  • Documentation: Comprehensive guides for each technology stack
  • Code Examples: Ready-to-run examples for each concept
  • Video Tutorials: Step-by-step walkthroughs for complex implementations
  • Community Forum: Platform for asking questions and sharing solutions
  • Office Hours: Weekly live sessions for additional support

Progress Tracking​

Students can track their progress through:

  • Completion of weekly exercises
  • Milestone achievements in the capstone project
  • Self-assessment quizzes
  • Peer feedback on collaborative projects

This curriculum follows the constitution principles of simulation-first development, embodied intelligence integration, and hands-on learning approach, ensuring students gain practical experience with real-world applications.