Introduction to Computer Vision
Extend your knowledge of Computer Vision through this free online course and apply it to work with real-time applications. It gives you fundamental and advanced-level knowledge to work with OpenCV for various AI tasks.
Skills you’ll Learn
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!
Course Outline
Computer Vision is one of the essential components of AI. This section explains how a computer system visualizes and understands images and videos. It also explains how every pattern is segmented and recognized by the machine and discusses different tasks employed in the process.
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.
This chapter discusses pixel intensity histograms, their philosophy, features, and process. It also demonstrates the convolution in different layers with its function and image filters. You will learn to obtain the result for an image using the convolution function.
This chapter explains different tasks in computer vision, which are-- classification, classification with localization, object detection, and instance segmentation to help you work with different applications of computer vision.
This chapter equips you with a thorough understanding of digital images, pixels, and amplitude quantization. It discusses the functions of converting analog spaces into digital images and sampling, and it then explains digital images and neighborhood concepts involved in computer vision with examples.
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Frequently Asked Questions
What jobs demand that you learn Computer Vision?
It is essential for every professional and aspirant in the machine learning and artificial intelligence sectors to have high competency in working with computer vision. The prevalent careers for the subject include
- Deep Learning and Computer Vision Engineer
- Image Processing Engineer
- Computer Vision Optimization Engineer
- Research Scientist - Computer Vision
- AI Engineer - Computer Vision
What are the steps to enroll in the Computer Vision course?
To learn Computer Vision concepts and knowledge to work on various platforms, you need to:
- Go to the course page
- Click on the “Enroll for Free” button
- Start learning Computer Vision course for free online.
Who is eligible to take this Computer Vision course?
Anybody with a basic understanding of Artificial Intelligence and Machine Learning and knowledge of Keras can take up this course.
Why choose Great Learning Academy to learn Computer Vision?
Data science, machine learning, artificial intelligence, product management, digital marketing, and big data engineering are among the subjects covered in the full-time and short-term programs offered by Great Learning, a top provider of ed-tech services. Some justifications for choosing Great Learning include the following:
- One of the few businesses, Great Learning, provides full-time, online, and offline training across various fields.
- You can get support for your learning journey from the experienced mentors on the Great Learning team who are specialists in their industry.
- The programs offered by Great Learning are created with consideration for the demands of the industry and are frequently updated to reflect the most recent developments.
Can I sign up for multiple courses from Great Learning Academy at the same time?
Yes. You can enroll in multiple courses simultaneously.