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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.

4.31
average rating

Ratings

Beginner

Level

0.75 Hrs

Learning hours

3.8K+

Learners

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! 

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Course Outline

Introduction to Computer Vision

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. 
 

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. 
 

Approaches to computer vision-Pixel Intensity Histograms and CNN

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.
 

Types of Computer Vision problems

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.
 

Digital Image and Pixels-Analog to digital Images Pixel Neighborhood

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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4.31
Course Rating
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Ratings & Reviews of this Course

Reviewer Profile

5.0

Great Experience That I Have Learned
It was a really helpful course to learn the basics of computer vision.
Reviewer Profile

5.0

It Was a Great Learning Experience
I liked the curriculum, the instructor's method of teaching, the topic depth, the quizzes, and the course content.
Reviewer Profile

4.0

My Learning Experience Is Really Good
The skills and tools taught in this course are good, and the course is easy to follow.

Introduction to Computer Vision

4.31
average rating

Ratings

0.75 Hrs

Learning hours

Beginner

Level

3.8K+

Learners

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:

  1. Go to the course page
  2. Click on the “Enroll for Free” button
  3. 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.   

Is there a limit on how many times I can take this Computer Vision course?

No, you can register for this course today and come back at your leisure to learn it for free online.  

How much does this Computer Vision course cost?

Introduction to Computer Vision is a free course. You can enroll in the course and start learning it online.
 

What knowledge and skills will I gain upon completing this Computer Vision course?

You will gain expertise in working with different techniques used in Computer Vision, hands-on experience working with Keras, and understanding how CV betters the traditional machine learning methods. You will understand CNN, different processes, Analog and Digital images carried out in different layers, and the concept of a fully connected layer. 
 

After completing this Computer Vision course, will I get a certificate?

Yes. The course constitutes different modules for different topics in computer vision with examples to work with AI and ML tasks, like digitizing images, sampling the data, quantizing, identification, classification, detection, padding, pooling, filtering, and transfer learning. Gain a thorough understanding of these concepts to earn a free Computer Vision certificate. 
 
 

What are the prerequisites to learning this Computer Vision course?

Before you learn this course, you must have basic knowledge of working with Keras and a good understanding of Artificial Intelligence and Machine Learning. 
 

How can a beginner learn Computer Vision?

Great Learning Academy offers a free course to learn Computer Vision with examples from basics online. The course includes an easy guide to learning concepts to work with Artificial Intelligence and Machine Learning tasks. 
 

What is the requirement to work with the Computer Vision technique?

You will need to have excellent computer vision image processing knowledge. Additionally, it will be favored if you have relevant skills to work with systems engineering, real-time computer vision techniques, and mathematics. This free course will, however, guide you through learning it online. 

Why is Computer Vision so popular?

Across many industries, computer vision is improving the convenience and ease of modern lives. Using computer vision, clients can produce relevant data by segmenting high-dimensional data from various human visual systems. This is an essential concept of artificial intelligence that primarily detects and recognizes certain things in photographs and videos. Due to the need to better understand how humans function and operate, what makes us unique, and how our carbon-based design can be copied to improve the world, computer vision as a field of study and application is a path to self-discovery.

Why is it essential to learn Computer Vision?

Computer vision is the study of simulating some of the complexity of the human visual system so that computers can recognize and analyze objects in images and videos in a way comparable to how the human brain does it. It is utilized in the security sector for facial identification and pattern detection, in the corporate sector, medical and automated vehicles. Applications of computer vision are extended in police departments and other law enforcement agencies to scan urban areas, examine the behavior of large groups, find suspicious activities, and spot possible threats before they happen. Facial recognition software heavily relies on computer vision, which enables computers to match images of people's faces to their identities. Computer vision algorithms find facial characteristics in photos and contrast them with face profile databases.
 

What are my next learning options after this Computer Vision course?

After you have completed this course, you can register for the AIML online courses and master them all under a single roof. 

 

Will I have lifetime access to this free Computer Vision online course?

Yes. You will have lifetime access to this online Computer Vision course once you enroll.
 

How long does it take to complete this free Computer Vision course?

Introduction to Computer Vision is half an hour-long course. You can, however, learn from the course at your convenience since it is self-paced.  
 

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