Free Computer Vision Course with Certificate
Computer Vision Essentials
Learn Computer Vision from basics in this free online training. This free Computer Vision course is taught hands-on. Learn about Image processing, OpenCV with Python & TensorFlow. Start now!
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6.75 Hrs
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About this course
This Computer Vision course is designed to ensure that you gain a thorough knowledge of image processing and how the OpenCV library is inculcated practically with Python to function in Artificial Intelligence and Machine Learning tasks. This course helps you understand the basics, such as sampling the data, digitizing images, and compressing or quantizing them. It will throw insights into different methods to work with pictures, including identification, classification, detection, and other processes in Computer Vision. Later, you will learn various Computer Vision applications to understand What Computer vision is. You will learn about Transfer Learning in the latter part of this course. After this self-paced beginner-level guide to Computer Vision, you can continue learning AI ML by registering for the Artificial Intelligence courses with millions of keen aspirants across the globe!
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Course Outline
Introduction to Computer Vision Essentials
This chapter begins by defining what Computer Vision is and then continues with its importance. It also discusses the connection of the digital world to the physical world and the sampling in the latter part with demonstrated examples.
What is Computer Vision?
In this chapter, you will understand computer vision, architecture, why, and how it is practiced. With examples, you will also gain knowledge about when and where the technology sees its application.
Digital Image
This chapter explains with examples the pixels and their color gradients used to work with data processing and pattern matching and recognition.
Process in Computer Vision
This chapter briefly explains convolution, relu, and pooling processes in Computer Vision, along with a demonstrated example.
Introduction to Pooling and Filters
You will learn to filter using different functions and obtain a diminished version of an image. You will then understand filtering and pooling with image functions in this section.
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