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RoboSupreme [Level - Master]
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Want to create robots that can move without human control? This course dives into autonomous robotics, where you’ll learn how robots perceive their surroundings and make navigation decisions independently. You’ll work with SLAM (Simultaneous Localization and Mapping), path planning, and LIDAR-based mapping to create self-driving robots. Using ROS and Gazebo simulations, you’ll build real-world projects that demonstrate how robots navigate complex environments. By the end of this course, you’ll have the skills to develop intelligent, autonomous robotic systems.
✅ What Will You Learn?
1. Perception and Environment Understanding
How Robots Perceive the World: Robots rely on sensors like LIDAR, cameras, and ultrasonic sensors to collect information about their surroundings. You’ll learn how to interpret this sensor data.
2. Navigation and Movement
Path Planning: Robots need to figure out how to move from one place to another while avoiding obstacles. You’ll learn about algorithms that help robots find the best path.
3. Real-World Applications
By the end of the course, you’ll understand how autonomous systems are used in industries like:
- Transportation: Self-driving cars and drones
- Warehousing and Logistics: Autonomous forklifts and delivery robots
- Healthcare: Service robots in hospitals
- Agriculture: Autonomous tractors and monitoring drones
What is Artificial Intelligence? How AI is Used in Robotics Overview of Machine Learning and Deep Learning Introduction to AI Tools: TensorFlow, OpenCV, and ROS
Understanding Machine Learning Algorithms Supervised vs. Unsupervised Learning Building and Training Your First Machine Learning Model Evaluating Model Performance
How Robots “See” the World Using Cameras and Sensors Image Processing with OpenCV Object Detection and Recognition Face Detection and Tracking
Introduction to Neural Networks and Deep Learning Building Convolutional Neural Networks (CNNs) Using Pre-trained AI Models for Faster Results Real-Time Object Detection with AI
Understanding Reinforcement Learning (RL) Concepts How Robots Learn by Trial and Error Training AI Agents in Simulations Implementing RL for Autonomous Decision-Making
How Robots Navigate Using AI Path Planning and Obstacle Avoidance Using AI for Simultaneous Localization and Mapping (SLAM) Implementing Autonomous Navigation with ROS
Build an Object Detection Robot with TensorFlow and OpenCV Create an Autonomous Path-Following Robot Using AI Develop a Smart Surveillance System with AI Monitoring Build a Reinforcement Learning Robot in a Virtual Environment
Choose a Project of Your Interest Receive Mentoring and Guidance Showcase Your AI-powered Robot Get Certified and Boost Your AI Robotics Portfolio
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Available Coaching Centers:
Learning Path
Earn Valuable Credentials
and Lead with a Competitive Edge.
Certificate and Recognition That Validates Your Skills
Our curriculum is meticulously designed in collaboration with industry leaders to ensure every skill you acquire is not just current, but in high demand.
Get Mentorship From Top 1 % Industry Experts
Our mentors are seasoned professionals and thought leaders who provide unparalleled guidance and personalized feedback.
Network For Lifelong Success
Our vibrant community of professionals offers continuous support, mentorship, and a platform for lifelong career acceleration.
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