AI5 PROFESSIONAL CERTIFICATE · BY TGC INDIA · UPDATED AUGUST 2026
Physical AI & Robotics with NVIDIA Isaac, ROS 2 & LeRobot
Build and test simulation-first robotics workflows covering perception, control, robot learning and safe deployment planning.
Online + OfflineWeekdays + WeekendsRegular + Fast Track
22+years in training
20,000+learners across TGC
5classroom locations
Live onlinejoin from anywhere
NEXT START OPTIONS
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COURSE OVERVIEW
What this course
is built to do.
Build simulation-first physical AI workflows using NVIDIA Isaac, ROS 2 and LeRobot, from robot models and sensor data to perception, control and learned policies.
Each module combines a live trainer demonstration, guided lab, assignment and review before the next stage.
CONNECTED CAREER DIRECTIONS
Physical AI EngineerRobotics Software DeveloperRobot Learning AssociateSimulation and Autonomy Engineer
IS THIS COURSE RIGHT FOR YOU?
Choose it for the right reason.
You know Python and want to enter robotics
You want simulation practice before touching hardware
You are interested in perception, control and learned robot behaviour
YOUR LEARNING ARC
From guided foundation to finished work.
Model
Set up robots, scenes, sensors and coordinate frames.
Connect
Use ROS 2 topics, services, actions and recorded data.
Learn
Build perception and imitation-learning experiments.
Validate
Test safety limits and present a simulation-first capstone.
INDUSTRY TASKS
Practise the work, not only the tool.
- Create an Isaac Sim robot and sensor scene
- Build a ROS 2 perception-to-action pipeline
- Train and evaluate a small LeRobot policy in simulation
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 a robot simulation
An Isaac Sim scene with documented sensors, frames and limits.
02
Develop with ROS 2
An observable node graph connecting perception and bounded control.
03
Train a robot-learning policy
A LeRobot experiment with dataset and failure analysis.
04
Validate a physical-AI system
A tested capstone and staged safety plan for optional hardware transfer.
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
5 learning modules
Build an embodied-AI pipeline in simulation, joining robot models, sensors, ROS 2 communication, perception, control and learned policies before any optional hardware transfer.
Physical AI foundations and simulation setup
Understand embodied systems and create a reproducible robot-development environment.
CORE TOPICS
- Physical AI, autonomy and robot-learning concepts
- Robot frames, kinematics and coordinate transforms
- NVIDIA Isaac Sim scenes, assets and sensors
- Simulation fidelity, repeatability and safety limits
GUIDED PRACTICE
Create a robot scene with camera and range sensors, then document assumptions and operating boundaries.
MODULE DELIVERABLE
Isaac Sim robot and sensor scene
ROS 2 communication and robot control
Connect software components through observable messages, services and actions.
CORE TOPICS
- Nodes, topics, services and actions
- Messages, QoS and launch files
- TF frames, bag recording and diagnostics
- Command limits, state machines and safe stops
GUIDED PRACTICE
Build a ROS 2 pipeline that reads a simulated sensor and commands a bounded robot action.
MODULE DELIVERABLE
ROS 2 perception-to-action package
Perception and scene understanding
Turn sensor streams into useful detections, positions and navigation decisions.
CORE TOPICS
- Camera calibration and image pipelines
- Detection, segmentation and depth
- Pose estimation and sensor fusion
- Dataset quality, uncertainty and failure cases
GUIDED PRACTICE
Implement and evaluate a simulated object-detection or navigation perception task.
MODULE DELIVERABLE
Robot perception experiment
LeRobot data and learned policies
Collect demonstrations and train a small policy while measuring where it fails.
CORE TOPICS
- Imitation learning and policy concepts
- Episode recording and dataset structure
- LeRobot training and evaluation workflow
- Overfitting, distribution shift and recovery
GUIDED PRACTICE
Record simulated demonstrations, train a policy and compare performance across changed scene conditions.
MODULE DELIVERABLE
LeRobot policy and evaluation report
Integration, safety and robotics capstone
Join perception, control and learning into a tested task with staged deployment criteria.
CORE TOPICS
- Task orchestration and state monitoring
- Simulation test suites and edge cases
- Human supervision and emergency handling
- Optional sim-to-real plan and project presentation
GUIDED PRACTICE
Build a simulation-first robot task, test normal and failure cases and present the evidence required before hardware use.
MODULE DELIVERABLE
Physical AI robotics 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
Guided practice brief
Plan, produce, test and present a finished piece with trainer feedback.
Individual application
Plan, produce, test and present a finished piece with trainer feedback.
Workflow build
Plan, produce, test and present a finished piece with trainer feedback.
Industry-style assignment
Plan, produce, test and present a finished piece with trainer feedback.
Quality review
Plan, produce, test and present a finished piece with trainer feedback.
Final capstone
Plan, produce, test and present a finished piece with trainer feedback.
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
NVIDIA Isaac SimROS 2LeRobotPython
Tool coverage may be updated when the industry changes. Core methods remain part of the course.COMMON QUESTIONS
Before you apply
Do I need a physical robot?
No. The main course is simulation-first; optional hardware exercises depend on local lab access.
＋What background is required?
Python, basic linear algebra and introductory machine learning are expected.
＋Does the course cover safety?
Yes. Operating limits, simulation tests, human supervision and staged hardware transfer are built into the project method.
＋Do I need coding experience?
No, unless the course level says otherwise. Your advisor will check the right starting level.
＋Are classes live or recorded?
Classes are trainer-led in the classroom or 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. Weekday, weekend and selected fast-track schedules are available.
＋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.