This YOLO Object Detection with Ultralytics Course introduces learners to modern real-time computer vision using the Ultralytics framework. It focuses on practical applications of YOLO models for object detection, pose estimation, and AI inference across different devices.
The course begins with an overview of YOLO models, including YOLOv8 and YOLO12, and explains their performance in terms of speed and accuracy. Learners will understand how different YOLO versions are used in real-time computer vision applications.
Students will explore real-time inference workflows, including running YOLO models on devices such as iPads and edge hardware like NVIDIA Jetson Nano. The course demonstrates how AI models can be deployed efficiently in mobile and embedded environments.
In addition, learners will compare YOLO pose estimation with other frameworks like MediaPipe to understand strengths and use cases in human pose detection. The course also introduces OCR (Optical Character Recognition) using AI and explains its advantages and limitations in real-world applications.
By the end of this course, learners will be able to use the Ultralytics package to build, test, and deploy YOLO-based computer vision systems for object d
