Hands-On Autonomous Vehicle Sensor Training Course Overview
This comprehensive four-week virtual course offers an in-depth exploration of common sensor types used in autonomous vehicle (AV) applications. Participants will gain hands-on experience by working with LiDAR, camera sensors, and neural networks, learning to interpret data, perform exercises such as line following and lane keeping, and complete object detection tasks using YOLO v3. The curriculum combines asynchronous video lectures by Dr. Venkat Krovi with live-online sessions led by Jeff Blackburn, providing both theoretical foundations and practical programming exercises. Learners will understand the importance of sensor redundancy in AVs and how to manipulate sensor data using tools like ROS and OpenCV. Optional weekly office hours are available to support participants through the program's rigorous content.
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