Jetson Nano Starter to Pro - A Computer Vision Course

This course begins with a thorough introduction to Jetson, highlighting its advantages over traditional microcontrollers like the Raspberry Pi. You'll learn how to select the right SD card, flash it effectively, and perform initial configurations to set the stage for advanced developments.

As you progress, delve into installing key AI libraries like OpenCV and PyTorch. Understand their roles in crafting robust AI solutions and enhance their performance with CUDA support. The course offers guidance on fundamental computer vision techniques, enabling seamless image operations, color conversions, and edge detections.

Explore object detection with YOLO and its variants through practical examples. Learn to train custom models like number plate recognition and optimize AI models using NVIDIA's TensorRT for enhanced performance. Dive deep into the DeepStream SDK for real-time video analysis and multi-camera synchronization, vital for security and surveillance applications.

Explore advanced topics like pose estimation, vehicle tracking, and face recognition, all with hands-on projects to reinforce learning. By the end, you will have mastered how to use this powerful platform to push the boundaries of what's possible in AI applications, making you a valuable asset in the tech industry.
What you will learn

Configure and initialize NVIDIA Jetson platforms
Compare Jetson with Raspberry Pi for technological advantages
Install and utilize key libraries like OpenCV and PyTorch on Jetson
Execute basic to advanced computer vision operations using OpenCV
Implement YOLO object detection on custom datasets
Integrate multiple camera inputs using RTSP and ONVIF protocols