Udemy – YOLOv8: Video Object Detection with Python on Custom Dataset 2024-3

Apr 18, 2025 - 19:51

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YOLOv8: Video Object Detection with Python on Custom Dataset Course. This comprehensive course teaches you how to use the advanced YOLOv8 model to detect objects in videos with Python. YOLOv8, which stands for “You Only Look Once,” is a deep convolutional neural network known for its speed and accuracy in processing images and videos. In this course, you will learn the basic concepts of object detection, the YOLOv8 architecture, and how to implement it on custom data. First, you will get an overview of the history of YOLO models and the differences between its different versions, then you will learn how to set up a development environment, prepare your data, and train the model. The course covers topics such as tuning model parameters, evaluating performance, testing on real videos, and methods for optimizing results. You will also learn how to apply the trained model to practical projects such as video surveillance, sports motion analysis, and autonomous systems. By completing practical projects throughout the course, you will gain the skills needed to use YOLOv8 in real-world applications. This course is designed for developers, AI engineers, and image and video processing enthusiasts, and requires a basic understanding of Python and machine learning. By the end of the course, you will be able to develop highly accurate object recognition systems and implement them in various projects.

What you will learn in the YOLOv8: Video Object Detection with Python on Custom Dataset course:

YOLOv8 for real-time video object recognition with Python
Learn, test YOLO8 on custom datasets, and deploy it in your own projects.
Identifying football, players, and referees in movies with Python
Vehicle detection (ambulance, bus, car, motorcycle, truck) in videos
What is YOLO and how does it work for object recognition?
YOLO family overview (YOLO2, YOLO3, YOLO4, YOLO5, YOLO6, YOLO7, YOLO8)
Overview of CNN, RCNN, Fast RCNN and Faster RCNN
Configuring a custom soccer player dataset for object recognition in movies
Configure a custom vehicle dataset for object detection in videos
YOLOv8 Ultralytics and its HyperParameter Settings
YOLOv8 training for player, referee and football recognition
Training YOLOv8 for vehicle detection (ambulance, bus, car, motorcycle, truck)
Testing trained YOLOv8 models on videos and images
Deploying YOLOv8: Export the model to the required format
What are the performance metrics for object recognition?
Calculation of performance metrics (Precision, Recall, Mean Average Precision mAP)

This course is suitable for people who:

This course is designed for computer vision enthusiasts, machine learning and deep learning specialists who want to delve into the world of video object recognition.
Whether you’re a beginner looking to build a strong foundation in object recognition or an experienced expert looking to enhance your skills, this course provides valuable insights and hands-on experience with YOLOv8, an advanced object recognition algorithm.

Course details YOLOv8: Video Object Detection with Python on Custom Dataset

Publisher: Udemy
Lecturer: Dr. Mazhar Hussain , AI & Computer Science School
Training level: Beginner to advanced
Training duration: 3 hours and 5 minutes
Number of lessons: 43

Course syllabus in 2025/2

Prerequisites for the YOLOv8: Video Object Detection with Python on Custom Dataset course

A Google Gmail account is required to get started with Google Colab to write Python Code
Python programming experience is an advantage but not required