Ultralytics YOLO Full Course – Object Detection, Pose Estimation & Real-Time AI Vision
عدد الدروس : 217 عدد ساعات الدورة : 03:30:01 شهادة معتمدة : نعم التسجيل في الدورة للحصول على شهادةللحصول على شهادة
- 1- التسجيل
- 2- مشاهدة الكورس كاملا
- 3- متابعة نسبة اكتمال الكورس تدريجيا
- 4- بعد الانتهاء تظهر الشهادة في الملف الشخصي الخاص بك
قائمة الدروس
عن الدورة
This Ultralytics YOLO course introduces modern computer vision techniques for real-time object detection, tracking, pose estimation, and AI-powered image analysis. The course focuses on practical applications using Ultralytics YOLO models and advanced vision technologies.
Learners begin by exploring how to use YOLO models for object detection with the Ultralytics Python package. The course discusses model performance, inference speed, and deployment considerations for real-time AI applications.
The series also covers YOLO pose estimation and compares it with MediaPipe for human pose tracking tasks. Additional topics include deploying YOLO models on edge AI devices such as NVIDIA Jetson Nano and Jetson Orin NX for efficient real-time inference.
The course introduces OCR systems powered by AI, explaining their strengths and limitations in text recognition tasks. It also explores Vision Language Models (VLMs), which combine image understanding with language reasoning capabilities.
Advanced topics include RT-DETR, a transformer-based real-time object detection model, and feature extraction algorithms such as SIFT used in classical computer vision.
Through short practical demonstrations and tutorials, learners gain insights into how modern AI vision systems are built and optimized for speed, accuracy, and deployment on different hardware platforms.
By the end of this course, learners understand how to use YOLO and related computer vision technologies for real-world AI applications.
