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13-Week Course Schedule

Overview​

This 13-week course schedule provides a structured learning path through the Physical AI & Humanoid Robotics curriculum. Each week builds upon the previous one, with hands-on exercises and projects to reinforce learning.

Week-by-Week Breakdown​

Week 1: ROS 2 Fundamentals​

  • Topics: ROS 2 architecture, nodes, topics, services
  • Reading: Module 1 Introduction
  • Hands-on: Complete chapter-01-ros2.ipynb notebook
  • Assignment: Create a simple ROS 2 publisher/subscriber system

Week 2: ROS 2 Advanced Concepts​

  • Topics: Actions, parameters, launch files, tools
  • Reading: Module 1 Advanced Topics
  • Hands-on: Extend Week 1 assignment with services and actions
  • Assignment: Build a simple robot control system

Week 3: ROS 2 Integration​

  • Topics: TF transforms, navigation stack, message types
  • Reading: Module 1 Integration
  • Hands-on: ROS 2 with external libraries
  • Assignment: Integrate external sensor data into ROS 2 system

Week 4: Simulation Environments​

  • Topics: Gazebo basics, model creation, physics
  • Reading: Module 2 Introduction
  • Hands-on: Create first simulation environment
  • Assignment: Build a simple robot model and simulate it

Week 5: Advanced Simulation​

  • Topics: Sensors in simulation, controllers, plugins
  • Reading: Module 2 Advanced Topics
  • Hands-on: Add sensors to simulated robot
  • Assignment: Implement sensor processing pipeline

Week 6: NVIDIA Isaac Introduction​

  • Topics: Isaac platform overview, Isaac ROS packages
  • Reading: Module 3 Introduction
  • Reading: Isaac ROS documentation
  • Assignment: Set up Isaac environment

Week 7: Isaac Perception​

  • Topics: Isaac perception packages, GPU acceleration
  • Hands-on: Use Isaac perception packages with simulated data
  • Assignment: Implement perception pipeline

Week 8: Isaac Navigation​

  • Topics: Isaac navigation stack, path planning
  • Hands-on: Navigation in Isaac Sim
  • Assignment: Create autonomous navigation system

Week 9: Vision-Language-Action Models​

  • Topics: VLA architecture, multimodal learning
  • Reading: Module 4 Introduction
  • Hands-on: Work with VLA models
  • Assignment: Train simple VLA model

Week 10: VLA Integration​

  • Topics: Connecting VLA to robotics platforms
  • Hands-on: Integrate VLA model with ROS 2
  • Assignment: Create language-guided robot behavior

Week 11: Simulation to Reality​

  • Topics: Domain transfer, reality gap, calibration
  • Reading: Simulation-to-reality techniques
  • Hands-on: Transfer simulation skills to real hardware
  • Assignment: Bridge simulation and real-world testing

Week 12: Advanced Integration​

  • Topics: Full system integration, optimization
  • Hands-on: Integrate all modules (ROS 2, Simulation, Isaac, VLA)
  • Assignment: Build complete robotic system

Week 13: Project and Evaluation​

  • Topics: Final project implementation and evaluation
  • Project: Implement a complete robotics application
  • Evaluation: Present project and discuss results

Prerequisites by Week​

Weeks 1-3: ROS 2​

  • Basic Python programming
  • Understanding of robotics concepts
  • Linux command line familiarity

Weeks 4-5: Simulation​

  • ROS 2 knowledge (Weeks 1-3)
  • Basic understanding of physics concepts
  • 3D modeling concepts (optional)

Weeks 6-8: NVIDIA Isaac​

  • ROS 2 knowledge (Weeks 1-3)
  • GPU computing basics
  • NVIDIA ecosystem familiarity (helpful but not required)

Weeks 9-10: VLA​

  • Machine learning basics
  • Deep learning concepts
  • Python and PyTorch/TensorFlow experience

Weeks 11-13: Integration​

  • All previous modules knowledge
  • Project management skills
  • Hardware debugging experience

Learning Path Flexibility​

Accelerated Track (8 weeks)​

  • Combine Weeks 1-2 into 1 week
  • Combine Weeks 4-5 into 1 week
  • Combine Weeks 6-7 into 1 week
  • Focus on key concepts and minimal hands-on

Extended Track (16 weeks)​

  • Add 3 additional weeks of advanced topics
  • Include more extensive hands-on projects
  • Add industry case studies and guest lectures

Assessment and Evaluation​

Weekly Assessments (40%)​

  • Hands-on exercises completed each week
  • Code quality and documentation
  • Understanding of concepts

Mid-term Project (25%)​

  • Integration of first two modules (ROS 2 and Simulation)
  • Presentation and code review

Final Project (35%)​

  • Complete integration of all four modules
  • Demonstration of VLA-guided robotic behavior
  • Final presentation and report

Resources by Week​

Week 1 Resources​

Week 4 Resources​

Week 6 Resources​

Week 9 Resources​

  • VLA model documentation
  • Research papers on VLA systems
  • Sample implementations and tutorials

Additional Support​

Office Hours​

  • Virtual sessions twice weekly
  • Q&A forums for each module
  • Peer collaboration opportunities

Extended Learning​

  • Research paper discussions
  • Industry guest speakers
  • Advanced project opportunities

Prerequisites Check​

Before starting Week 1, ensure you have:

  • Python 3.10+ installed
  • Git version control system
  • Basic command line skills
  • Access to appropriate hardware or cloud resources
  • Docusaurus development environment set up