AI5 ACADEMY PROFESSIONAL CERTIFICATE · A TGC INDIA INITIATIVE · UPDATED SEPTEMBER 2026
Physical AI & Robotics with NVIDIA Isaac, ROS 2, GR00T & LeRobot Course
Learn how AI moves from the computer into the physical world: program robots, simulate them, give them vision, make them navigate and manipulate objects, teach them behaviours, and understand how those systems move from simulation toward real hardware.
12 Weeks | 3 Live Sessions/Week | 60–90 Minutes/Session | 6 Practical Projects
Basic Python Required | Physical Robot Not Required
Learn ROS 2 + NVIDIA Isaac + LeRobot through practical robotics projects.
Build → Simulate → See → Navigate → Manipulate → Learn → Deploy
IntermediateLive OnlineSimulation-based learning
22+years in training
20,000+learners across TGC
5classroom locations
Live onlinejoin from anywhere
NEXT START OPTIONS
Choose a live batch.
COURSE OVERVIEW
What this course
is built to do.
Learn how AI moves from the computer into the physical world: program robots, simulate them, give them vision, make them navigate and manipulate objects, teach them behaviours, and understand how those systems move from simulation toward real hardware.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
SKILLS RELEVANT TO CAREER PATHS INCLUDING
Robotics Software EngineerROS 2 DeveloperRobotics AI EngineerRobotics Simulation EngineerAutonomous Systems EngineerRobot Perception / Computer Vision rolesPhysical AI EngineerRobotics Research roles
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You know basic Python and want practical robotics experience
You want to learn through simulation without buying a robot
You want to connect programming, perception, navigation, manipulation and robot learning
YOUR LEARNING ARC
From guided foundation to finished work.
Build
Program robot communication and control.
Simulate
Create virtual robots and environments.
See
Identify and locate objects.
Navigate
Map, plan routes and avoid obstacles.
Manipulate
Grasp and move objects.
Learn
Train and test behaviours from demonstrations.
Deploy
Understand testing and the route toward physical hardware.
INDUSTRY TASKS
Practise the work, not only the tool.
- Build a ROS 2 workflow that communicates with and controls a simulated robot.
- Create a robot and environment with sensors and physical interaction inside Isaac Sim.
- Create a perception workflow that identifies and locates objects.
- Map a simulated environment, localize the robot, plan routes and avoid obstacles.
- Use demonstration data to train/test a small manipulation policy in a compatible simulation workflow.
- Combine simulation, ROS 2, perception and robot intelligence; present tests and a staged hardware-transfer plan. Choose a mobile-robot or robotic-arm capstone where suitable.
PRO
LED
LED
YOUR TRAINING TEAM
Learn from experienced working professionals.
Live demonstrations, guided practice and direct project feedback are part of the course. Trainers update examples and tool coverage as professional practice changes.
WHAT YOU WILL BE ABLE TO DO
Course outcomes
01
Build ROS 2 robotics applications
Demonstrate through guided exercises, project tests and the capstone presentation.
02
Create and control simulated robots
Demonstrate through guided exercises, project tests and the capstone presentation.
03
Work with NVIDIA Isaac Sim
Demonstrate through guided exercises, project tests and the capstone presentation.
04
Connect ROS 2 with simulation workflows
Demonstrate through guided exercises, project tests and the capstone presentation.
05
Create robot perception systems
Demonstrate through guided exercises, project tests and the capstone presentation.
06
Work with cameras and simulated sensors
Demonstrate through guided exercises, project tests and the capstone presentation.
07
Implement mapping and autonomous navigation concepts
Demonstrate through guided exercises, project tests and the capstone presentation.
08
Create basic robotic manipulation workflows
Demonstrate through guided exercises, project tests and the capstone presentation.
09
Work with LeRobot datasets and robot policies
Demonstrate through guided exercises, project tests and the capstone presentation.
010
Understand imitation-learning workflows
Demonstrate through guided exercises, project tests and the capstone presentation.
011
Understand GR00T and VLA-based robotics
Demonstrate through guided exercises, project tests and the capstone presentation.
012
Understand the process of moving from simulation toward physical hardware
Demonstrate through guided exercises, project tests and the capstone presentation.
013
Build a portfolio-ready Physical AI capstone project
Demonstrate through guided exercises, project tests and the capstone presentation.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
DETAILED COURSE FLOW
10 learning modules
Build → Simulate → See → Navigate → Manipulate → Learn → Deploy
Week 1 — Physical AI & Robotics Foundations
Understand how AI connects sensing to physical action.
CORE TOPICS
- Physical AI and embodied AI
- How intelligent robots work
- Sensors, actuators and controllers
- Perception → reasoning → planning → action
- Mobile robots and robotic arms
- Physical AI industry applications
GUIDED PRACTICE
Trace a simulated robot task from sensor input to action.
MODULE DELIVERABLE
Robot workflow map
Weeks 2–3 — Python & ROS 2 for Robotics
Program and connect robot components.
CORE TOPICS
- Python for robotics
- ROS 2 architecture, nodes and packages
- Topics and publishers/subscribers
- Services and actions
- Robot control
- URDF/Xacro
- Coordinate frames
- Visualization and debugging
- ROS 2 practical workflows
GUIDED PRACTICE
Build a ROS 2 workflow that communicates with and controls a simulated robot.
MODULE DELIVERABLE
ROS 2 Controlled Robot
Week 4 — Robot Modelling & Simulation
Build a virtual robot and understand its movement.
CORE TOPICS
- Robot models
- Joints and links
- Physics
- Cameras and sensors
- Virtual environments
- Simulation fundamentals
GUIDED PRACTICE
Configure joints, sensors and physical limits in a virtual environment.
MODULE DELIVERABLE
Robot model and simulation setup
Weeks 5–6 — NVIDIA Isaac Sim
Create and test a digital robot in a sensor-rich scene.
CORE TOPICS
- Isaac Sim environment
- Robot simulation
- Cameras and depth sensors
- LiDAR
- Physics simulation
- Synthetic data
- Robot/environment interaction
- ROS 2 integration
GUIDED PRACTICE
Create a robot and environment with sensors and physical interaction inside Isaac Sim.
MODULE DELIVERABLE
NVIDIA Isaac Sim Digital Robot
Week 7 — Robot Perception & Isaac ROS
Give a robot useful information about nearby objects.
CORE TOPICS
- Computer vision for robots
- OpenCV
- Object detection
- Depth perception
- Pose estimation
- Isaac ROS
- GPU-assisted perception workflows
GUIDED PRACTICE
Create a perception workflow that identifies and locates objects.
MODULE DELIVERABLE
AI Vision Robot
Week 8 — Autonomous Navigation
Help a mobile robot move through its environment.
CORE TOPICS
- Mapping
- Localization
- SLAM
- Path planning
- Obstacle avoidance
- Autonomous navigation
- ROS 2 navigation workflows
GUIDED PRACTICE
Map a simulated environment, localize the robot, plan routes and avoid obstacles.
MODULE DELIVERABLE
Autonomous Navigation Robot
Week 9 — Robotic Arms & Manipulation
Control a robot arm for a bounded task.
CORE TOPICS
- Robot arm fundamentals
- Joints and end effectors
- Manipulation
- Grasping
- Pick-and-place
- Manipulation in simulation
GUIDED PRACTICE
Build and test a simulated pick-and-place sequence.
MODULE DELIVERABLE
Simulated manipulation exercise
Week 10 — LeRobot & Robot Learning
Teach a small robot policy from demonstrations.
CORE TOPICS
- Hugging Face LeRobot
- Robot datasets
- Recording demonstrations
- Imitation learning
- Robot policies
- Training and evaluating robot behaviours
- Using existing datasets when physical hardware is unavailable
GUIDED PRACTICE
Use demonstration data to train/test a small manipulation policy in a compatible simulation workflow.
MODULE DELIVERABLE
LeRobot Pick-and-Place
Week 11 — Isaac Lab, GR00T & Modern Physical AI
Get practical, introductory exposure to modern robot learning.
CORE TOPICS
- NVIDIA Isaac Lab
- Robot-learning workflows
- NVIDIA GR00T
- Vision-language-action concepts
- Multimodal robot intelligence
- Natural-language robot instructions
- Current Physical AI workflows
GUIDED PRACTICE
Run a guided robot-learning example and inspect how visual and language inputs relate to actions. Use existing models; advanced research and large-model training are outside the core scope.
MODULE DELIVERABLE
Guided Isaac Lab and GR00T/VLA walkthrough
Week 12 — Sim-to-Real & Capstone
Integrate the workflow and explain the next steps toward hardware.
CORE TOPICS
- Simulation-to-real concepts
- Moving from virtual robot to hardware
- NVIDIA Jetson introduction
- Sensors and physical deployment
- Testing and safety
- Capstone integration
- Project presentation
GUIDED PRACTICE
Combine simulation, ROS 2, perception and robot intelligence; present tests and a staged hardware-transfer plan. Choose a mobile-robot or robotic-arm capstone where suitable.
MODULE DELIVERABLE
Physical AI Capstone
HOW THE TRAINING WORKS
Learn it. Apply it. Get it reviewed. Improve it.
Every important skill moves through explanation, demonstration, guided use and independent application. Trainer feedback is used to revise the work before it becomes part of the final portfolio.
Concept briefing
The trainer explains the principle, use case, limitations and the quality standard expected.
Live demonstration
A complete task is demonstrated while the trainer explains decisions, checks and common mistakes.
Guided lab
Learners repeat the method with support, ask questions and correct problems during the session.
Applied assignment
The same method is used on a different brief so the learner must make independent decisions.
Review and revision
Work is checked against a rubric, revised after feedback and prepared for project presentation.
PROGRESS IS CHECKED THROUGHClass exercisesModule deliverablesProject reviewsFinal capstone presentation
PORTFOLIO WORK
Projects you can show
ROS 2 Controlled Robot
Build a ROS 2 workflow that communicates with and controls a simulated robot.
NVIDIA Isaac Sim Digital Robot
Create a robot and environment with sensors and physical interaction inside Isaac Sim.
AI Vision Robot
Create a perception workflow that identifies and locates objects.
Autonomous Navigation Robot
Map a simulated environment, localize the robot, plan routes and avoid obstacles.
LeRobot Pick-and-Place
Use demonstration data to train/test a small manipulation policy in a compatible simulation workflow.
Physical AI Capstone
Combine simulation, ROS 2, perception and robot intelligence; present tests and a staged hardware-transfer plan. Choose a mobile-robot or robotic-arm capstone where suitable.
TAKE THE NEXT STEP
Need fees, syllabus or the right batch?
An AI5 Academy advisor can help you compare mode, schedule and starting level.
TOOLS COVERED
PythonROS 2NVIDIA Isaac SimNVIDIA Isaac ROSNVIDIA Isaac LabHugging Face LeRobotOpenCVPyTorchGit/GitHub
Tool coverage may be updated when the industry changes. Core methods remain part of the course.BEFORE WEEK 1
Prepare for practical robotics
Students can complete the core course using simulation. Purchasing a physical robot is not required.
Recommended short pre-course preparation module for learners who need it: Python variables, loops, functions and packages; Ubuntu files, installation basics and terminal commands; robotics sensors, actuators, coordinates and control basics. Practise running a Python script, navigating folders in the terminal and explaining a simple sensor-to-action loop before Week 1.
No previous ROS 2, NVIDIA Isaac or LeRobot experience is needed. Robot ownership and NVIDIA Jetson hardware are not required.
YOUR WORKING STACK
Software and optional hardware
Core Software
Python · ROS 2 · NVIDIA Isaac Sim · NVIDIA Isaac ROS · NVIDIA Isaac Lab · Hugging Face LeRobot · OpenCV · PyTorch · Git/GitHub
Modern Physical AI Exposure
NVIDIA GR00T · Vision-Language-Action models · Imitation learning · Robot policies
Practical, introductory NVIDIA GR00T training uses guided examples and existing models. Large-scale research training is outside the core course.
Optional Hardware
NVIDIA Jetson · Cameras/depth cameras · Robotic arms · Mobile robots · Sensors
Hardware purchases are optional. Any AI5 hardware or lab exposure must be confirmed for the batch.
Physical AI Terms Made Simple
ROS 2
Communication system connecting different parts of a robot.
Isaac Sim
NVIDIA’s virtual environment for building and testing robots.
Isaac ROS
NVIDIA tools that help ROS 2 robots process AI and sensor data.
LeRobot
Open-source tools for training robots using demonstrations and datasets.
SLAM
Helps a robot create a map while working out where it is.
GR00T
NVIDIA technology for developing AI models that can understand and perform physical tasks.
Sim-to-Real
Building and testing in simulation before transferring the workflow to a physical robot.
VLA
AI that connects what a robot sees and is told with the physical action it should perform.
System requirements and access costs
For local Isaac Sim 6.0, NVIDIA lists a GeForce RTX 4080 with 16 GB VRAM, 32 GB RAM and 50 GB SSD as minimum specifications. Its “Good” tier lists an RTX 5080, 64 GB RAM and 500 GB SSD. Supported desktop systems include Ubuntu 22.04/24.04 and Windows 11; containers require Linux. Robot-learning workloads may need more memory.
Use the compatibility checker and confirm the batch’s software versions before buying equipment. A compatible remote RTX workstation or cloud instance can replace a local GPU; rental charges may apply. Existing datasets support LeRobot practice without a physical robot, but they do not remove the compute needs of Isaac Sim labs. Confirm GPU access and any additional charges with AI5 before enrolment.
NVIDIA system requirements and compatibility checker ↗
NVIDIA Isaac Sim licensing FAQ ↗ · Checked September 2026.
Connect your AI skills to robotics
Build supporting skills through Python for AI, Machine Learning, Computer Vision, Generative AI and Agentic AI. This Physical AI and robotics course is AI5’s main route for robotics-focused NVIDIA Isaac Sim training, ROS 2 and LeRobot.
COMMON QUESTIONS
Before you apply
Do I need to purchase a robot?
No. Students can complete the core course using simulation. Purchasing a physical robot is not required.
＋Do I need an NVIDIA GPU?
Local Isaac Sim work needs a supported NVIDIA RTX GPU. A compatible remote GPU workstation or cloud instance is an alternative; rental costs may apply. Check the separate system guidance below and confirm access and costs with AI5 before enrolling. A basic laptop alone should not be assumed to run Isaac Sim.
＋Are ROS 2 and LeRobot paid?
ROS 2 and Hugging Face LeRobot are open-source. Computing, cloud rental and optional hardware can still involve costs.
＋Is NVIDIA Isaac Sim paid?
NVIDIA describes Isaac Sim as open source and free for internal R&D and development. Bundled components have separate terms; redistribution or providing Isaac Sim with Omniverse Kit as a service can require an NVIDIA AI Enterprise licence. Cloud computing and support may cost extra. See the official NVIDIA licensing FAQ linked below; checked September 2026.
＋Will I work with a real robot?
Core teaching and assessment use simulation. Physical robot, Jetson or lab exposure is optional and only available if AI5 confirms the arrangement for your batch. It is not included as a guaranteed part of the core course.
＋What background is required?
Basic Python/programming familiarity and comfort learning technical software are required. Linux/Ubuntu, AI/ML fundamentals and electronics, automation or robotics exposure are helpful, not mandatory. No previous ROS 2, NVIDIA Isaac or LeRobot experience is required.
＋How are the 12 weeks delivered?
Live Online, with 3 instructor-led sessions per week lasting 60–90 minutes each: approximately 36 live sessions and 36–54 instructor-led hours. Practical assignments and projects require work outside live classes.
＋Can I prepare before joining?
Yes. We recommend a short pre-course preparation module: Python variables, loops, functions and packages; Ubuntu installation basics, files and terminal commands; and robotics sensors, actuators, coordinates and control basics. Complete small exercises before Week 1 if you need preparation.
＋Does the course guarantee a robotics job?
No. It develops skills relevant to robotics career paths. Hiring depends on your wider education, experience and portfolio; 12 weeks alone does not make a learner a senior robotics engineer.
＋Are classes live or recorded?
Classes are instructor-led Live Online.Recordings may support revision but do not replace class.
＋Will I receive a certificate?
Yes. Course completion requires attendance, assignments and the final project.
＋Can working professionals join?
Yes. The programme runs for 12 weeks with three live sessions each week. Confirm suitable timings before enrolment.
＋NEXT BATCH
Choose your course.
Choose your schedule.
Online or offline. Weekdays or weekends. Regular or fast track. Speak with an AI5 Academy advisor about the right starting level.
COURSE PLANNING
Physical AI & Robotics with NVIDIA Isaac, ROS 2, GR00T & LeRobot Course: syllabus, projects and admission details
Learn how AI moves from the computer into the physical world: program robots, simulate them, give them vision, make them navigate and manipulate objects, teach them behaviours, and understand how those systems move from simulation toward real hardware.
Physical AI & Robotics with NVIDIA Isaac, ROS 2, GR00T & LeRobot Course syllabus
Week 1 — Physical AI & Robotics Foundations, Weeks 2–3 — Python & ROS 2 for Robotics, Week 4 — Robot Modelling & Simulation. Read the full curriculum above for the complete learning sequence.
Physical AI & Robotics with NVIDIA Isaac, ROS 2, GR00T & LeRobot Course projects
ROS 2 Controlled Robot; NVIDIA Isaac Sim Digital Robot; AI Vision Robot. Check the project section for the work expected in this program.
Physical AI & Robotics with NVIDIA Isaac, ROS 2, GR00T & LeRobot Course eligibility
Entry level: Intermediate. Ask a counsellor to confirm whether your background meets the program prerequisites.
Physical AI & Robotics with NVIDIA Isaac, ROS 2, GR00T & LeRobot Course duration
Program duration: 12 weeks. Confirm the next batch timetable before joining.
Physical AI & Robotics with NVIDIA Isaac, ROS 2, GR00T & LeRobot Course tools
Python, ROS 2, NVIDIA Isaac Sim, NVIDIA Isaac ROS, NVIDIA Isaac Lab, Hugging Face LeRobot. Tool access and any paid accounts should be confirmed for your cohort.
Physical AI & Robotics with NVIDIA Isaac, ROS 2, GR00T & LeRobot Course fees and batches
Training mode: Live Online. Request current fees, available batches and a suitable schedule.
Get course details →