AI in Self-Driving Cars & Robotics
Discover how artificial intelligence powers the future of mobility and robotics. Learn how self-driving cars perceive and navigate the world, and how intelligent robots perform precise, complex tasks—unlocking the potential of AI-driven technology in real life.
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Skill Pathshala Team - 230 enrolled students
Course Description
AI in Self-Driving Cars & Robotics is a comprehensive course that explores how artificial intelligence is transforming transportation and automation. From autonomous vehicles to intelligent robots, AI enables machines to perceive, decide, and act with precision. This course combines theory with practical applications to help learners understand the technologies driving the future of mobility and robotics.
You will gain hands-on knowledge of AI techniques, machine learning, computer vision, and control systems that allow vehicles and robots to navigate complex environments, detect objects, and make intelligent decisions. Real-world case studies and examples ensure that the concepts are easy to understand and applicable.
What you'll learn in this course
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Fundamentals of AI and its role in autonomous vehicles and robotics
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Computer vision for object detection, recognition, and tracking
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Sensor fusion: integrating LiDAR, RADAR, GPS, and camera data
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Path planning and control algorithms for safe navigation
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Machine learning and deep learning applications in robotics and self-driving cars
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Programming and simulation of autonomous systems
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Real-world case studies of autonomous cars, drones, and industrial robots
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Safety, ethical, and regulatory considerations in AI-driven machines
Requirements
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Basic programming knowledge (Python recommended)
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Understanding of mathematics (linear algebra, probability, basic calculus)
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Interest in robotics, AI, and autonomous systems
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Laptop or PC with internet access; GPU recommended for deep learning exercises
Curriculum
- 7 Lessons
- 60 mins.
- Overview of Artificial Intelligence and its applications
- Understanding autonomous vehicles and intelligent robots
- Key components: sensors, actuators, and control systems
- Real-world examples of AI in mobility and robotics
- Future trends and career opportunities
- Introduction to machine learning and deep learning
- Supervised, unsupervised, and reinforcement learning basics
- Neural networks and their role in autonomous systems
- Data collection and preprocessing for AI models
- Model evaluation and performance metrics
- Basics of computer vision and image processing
- Object detection and recognition (vehicles, pedestrians, obstacles)
- Tracking and prediction algorithms
- Image segmentation and scene understanding
- Applications in self-driving cars and robotic arms
- Types of sensors: LiDAR, RADAR, GPS, ultrasonic, cameras
- How sensors work individually and together
- Sensor fusion techniques for accurate perception
- Handling noisy or incomplete sensor data
- Real-time sensor data processing
- Motion planning algorithms for vehicles and robots
- Lane keeping, obstacle avoidance, and trajectory generation
- Feedback control and PID controllers
- Autonomous navigation strategies
- Simulating and testing control systems
- Robotic perception and decision-making
- Manipulation, pick-and-place, and assembly tasks
- Integration of AI with robotic arms and mobile robots
- Human-robot interaction and safety considerations
- Case studies of industrial and service robots
- Autonomous driving levels and capabilities
- Decision-making under dynamic environments
- Advanced driver assistance systems (ADAS)
- Simulation environments for self-driving cars
- Real-world deployment challenges and safety
Your Instructor
Skill Pathshala Team
Advanced Educator
Skill Pathshala is an online learning community with thousands of classes for creative and curious people, on topics including illustration, design, programming, photography, video, freelancing, and more. On Skill Pathshala, members come together to find inspiration and take the next step in their creative journey.
- Duration span 60 mins.
- Lectures0
- LanguageEnglish
- Skill levelMedium
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