Pluralsight – Learning Path – Computer Vision for Developers 2024-8

Description

Learning Path – Computer Vision for Developers course. This course introduces you to the exciting world of computer vision. Computer vision is a subset of artificial intelligence that teaches computers to understand and interpret the world around them visually. This course is designed for developers who want to add advanced vision capabilities to their applications. In this course, you will learn how to perform a variety of image classification, segmentation, and object detection tasks in Python. You will also learn how to implement image processing methods in OpenCV and Pillow. Available courses in this path:

• Image Representation and Processing
• Image Segmentation
• Object Detection Recognition and Tracking
• Ethics for Computer Vision
• Neural Networks for Image Classification

What you will learn

• How to display digital images and process them for different applications
• How to identify and track objects in an image or video
• How to consider ethical issues in computer vision applications
• How to use neural networks for image classification

This course is suitable for people who

• Developers who want to add image recognition capabilities to their applications.
• Artificial intelligence and machine learning enthusiasts who want to specialize in computer vision.
• People who want to be aware of the latest developments in the field of computer vision.

Learning Path – Computer Vision for Developers course specifications

• Publisher: Pluralsight
• Instructor: Pratheerth Padman , David Clinton , Xavier Morera , Bogdan Sucaciu , Axel Sirota
• Training level: beginner to advanced
• Training duration: 2 hours and 42 minutes
• Number of courses: 47

Headlines of the course on 9/2024

Learning Path – Computer Vision for Developers course prerequisites

• Learners should be comfortable coding in Python and know how to perform basic data manipulation tasks.

Course images

Sample video of the course

download link

Download file – 421 MB

File(s) password: www.downloadly.ir

File size

421 MB