Artificial Intelligence in Autonomous Vehicles
( 25 Modules )

Module #1
Introduction to Autonomous Vehicles
Overview of autonomous vehicles, history, and applications

Module #2
AI in Autonomous Vehicles
Introduction to AI in autonomous vehicles, benefits, and challenges

Module #3
Sensors and Perceptions
Overview of sensors used in autonomous vehicles, such as cameras, lidar, and radar

Module #4
Computer Vision Fundamentals
Introduction to computer vision, image processing, and feature extraction

Module #5
Object Detection in Images
Object detection techniques, such as YOLO, SSD, and Faster R-CNN

Module #6
Object Tracking in Videos
Object tracking techniques, such as Kalman filter and particle filter

Module #7
_SLAM (Simultaneous Localization and Mapping)
Introduction to SLAM, types, and applications in autonomous vehicles

Module #8
Machine Learning Fundamentals
Introduction to machine learning, supervised and unsupervised learning, and deep learning

Module #9
Neural Networks for Autonomous Vehicles
Introduction to neural networks, convolutional neural networks, and recurrent neural networks

Module #10
Deep Learning for Object Detection
Deep learning techniques for object detection, such as CNN and YOLO

Module #11
Motion Planning and Control
Introduction to motion planning and control, trajectory planning, and control systems

Module #12
Decision-Making for Autonomous Vehicles
Decision-making techniques, such as rule-based systems and behavior trees

Module #13
Sensor Fusion and Calibration
Overview of sensor fusion, sensor calibration, and sensor validation

Module #14
Autonomous Vehicle Software Architecture
Overview of software architecture, ROS, and Autoware

Module #15
Safety and Security in Autonomous Vehicles
Overview of safety and security concerns, regulations, and standards

Module #16
Testing and Validation of Autonomous Vehicles
Overview of testing and validation methods, simulation, and scenario-based testing

Module #17
Autonomous Vehicle Regulations and Standards
Overview of regulations, standards, and guidelines for autonomous vehicles

Module #18
Ethics in Autonomous Vehicles
Overview of ethical considerations, value alignment, and moral dilemmas

Module #19
Autonomous Vehicle Deployment and Maintenance
Overview of deployment, maintenance, and update strategies

Module #20
Autonomous Vehicle Business Models
Overview of business models, market trends, and use cases

Module #21
Case Studies:Autonomous Vehicle Applications
In-depth analysis of autonomous vehicle applications, such as trucking, ride-hailing, and agriculture

Module #22
Case Studies:Autonomous Vehicle Companies
In-depth analysis of autonomous vehicle companies, such as Waymo, Tesla, and Cruise

Module #23
Project:Autonomous Vehicle System Design
Design and develop an autonomous vehicle system using learned concepts

Module #24
Project:Autonomous Vehicle System Implementation
Implement and test an autonomous vehicle system using learned concepts

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Artificial Intelligence in Autonomous Vehicles career

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Artificial Intelligence in Autonomous Vehicles ( 25 Modules )

Artificial Intelligence in Autonomous Vehicles
( 25 Modules )