Best Computer Vision Courses for Beginners

7 Best Computer Vision Courses for Beginners in 2022

Hello folks, If you want to learn Computer Vision and OpenCV from scratch and looking for the best computer vision online courses from Udemy, Coursera, and Pluralsight then you have come to the right place.

Earlier, I have shared the best online courses to learn Python, Data Science, and Machine Learning from Coursera and Udemy, and in this article, I am going to share the best online training courses to learn both Computer Vision and OpenCV.

The list includes courses for both beginners and experienced programmer who wants to learn the advanced concept of Computer Vision and Open CV.

It’s one of the most existing fields of Machine Learning and Artificial Intelligence and has uses across industries like object detection, self-driving cars, robotics, and much more.

If you don’t know, Computer vision simply is the science or field of making the machine see and detect, track, classify, analyze objects, or any tasks that are related to process images and videos. And, OpenCV is a popular Python library that allows you to do things like image filtering and much more.

Learning computer vision allows you to master one of the master fields that on-demand today and lets you create amazing projects in different areas such as self-driving cars, disease diagnoses like cancers, create intelligent weapon guidance systems that become widely used in militaries today, and much more.

In this article, you will learn many online courses that allow you to master computer vision and some of them will show you how to implement deep learning with computer vision to be more accurate, and the good thing about these courses is that each one has its unique programming language that is used to perform these tasks of processing images and videos.

1. Python for Computer Vision with OpenCV [Udemy best Coures]

This is one of the best Udemy course to learn Computer Vision and OpenCV library for Python developers. This class will walk you into the basics of how to use python with OpenCV to learn the methods used to analyze and detect objects inside a picture or a video.

This course is created by none other than Jose Portilla, instructor of Complete Python Bootcamp and The Complete SQL Bootcamp courses on Udemy, both courses have been joined by millions of developers.

Here are the things you will learn in this course:

• The basics of computer vision (OpenCV)
• Create recognition software like face detection.
• Use deep learning to develop an image classifier.

The class will get you from the start on how to use OpenCV and how to work with images then teaches you how to develop many different applications such as face detection, object detection, and Streaming video with OpenCV.

Here is the link to join this awesome course — Python for Computer Vision with OpenCV

2. Deep Learning and Computer Vision A-Z [Udemy Course]

This is another fantastic Udemy course to learn Computer Vision and Deep Learning. In this course, you won’t only master how to use OpenCV with the python programming language but also you will learn deep learning in practice and how to implement it with computer vision and what is special in this course.

The course shows you a bunch of tools that used in computer vision alongside OpenCV and then implement Artificial intelligence to create some programs like accurate face detection software, object detection, and image creation using AI.

Here are the key things you will learn in this course:

1. Face and object detection software with OpenCV.
2. Implement deep learning with computer vision.
3. Learning Artificial Intelligence.

Overall a great course to learn Deep Learning and Computer Vision on Udemy in 2021. This is also a very affordable course and you can get in just $10 on Udemy sales which happens every now and then.

Here is the link to join this course OpenCV courses — Deep Learning and Computer Vision A-Z

3. Computer Vision Basics — Coursera [Free Course]

If you are familiar with Matlab and you want to begin your adventure in computer vision then this program is the right for you since it will teach you the basics of computer vision and how to implement it with Matlab.

The course teaches you the crucial element of how humans see and how the machine can implement this to do computer vision tasks and then will walk you into some code to get hands-on experience on that topic. You will get a free license to install Matlab during the course period.

You will learn in this course:

1. How humans can see and react in the real world.
2. How computer vision mimics humans in object recognition.
3. Implement computer vision in Matlab code.

This is a free Coursera course and you can enroll for Free. This Computer Vision course is offered by the University of Buffalo and the State University of New York.

Here is the link to join this awesome course — Computer Vision Basics

4. Getting Started with OpenCV in .NET [Plurlasight best course]

In this course, you will learn how to use OpenCV with the .NET framework developed by Microsoft and it will show you write some code in C++ programming languages that belong to Microsoft and it’s packaged.

You will write codes for object detection, motion detection, face detection, and recognition and then shows you how to use NVidia Cuda in order to speed up the process of computer vision.

Here are the things you will learn in this course:

1. How computer vision works.
2. Write computer vision codes with the .NET framework.
3. Implement NVidia Cuda to your programs.

Here is the link to join this course on Pluralsight — Getting Started with OpenCV in .NET

5. Introduction to Computer Vision with Watson and OpenCV

If you want to learn computer vision with python and you want to install all of that libraries one by one then you should see this online OpenCV and Watson course on Coursera that will let you create your programs on the cloud directly.

This course will teach you about image processing, classification, and how robots with computer vision can interact with pictures with Python and OpenCV, and later you will transform this program into a web application and deploy it on the cloud.

You will learn in this course:

1. Computer vision and its various applications.
2. Create a computer vision program with python and OpenCV.
3. Deploy your code to the cloud.

This Coursera Computer Vision course is also part of the IBM Applied AI Professional Certificate and it's offered by none other than IBM, one of the most reputed and old tech companies and also the company behind Watson AI.

Here is the link to join this course — Introduction to Computer Vision with Watson and OpenCV

6.Advanced Computer Vision with TensorFlow

In this course, you will:

a) Explore image classification, image segmentation, object localization, and object detection. Apply transfer learning to object localization and detection.

b) Apply object detection models such as regional-CNN and ResNet-50, customize existing models, and build your own models to detect, localize, and label your own rubber duck images.

c) Implement image segmentation using variations of the fully convolutional network (FCN) including U-Net and d) Mask-RCNN to identify and detect numbers, pets, zombies, and more.

d) Identify which parts of an image are being used by your model to make its predictions using class activation maps and saliency maps and apply these ML interpretation methods to inspect and improve the design of a famous network, AlexNet.

The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture and tools that help them create and train advanced ML models.  

This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models.

Here is the link to join this course:-Advanced Computer Vision with TensorFlow

7.Deep Learning in Computer Vision.

Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars. 

The goal of this online course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In the course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and often demonstrated in movies and TV-shows example of computer vision and AI.

Do you have technical problems? Write to us: coursera@hse.ru

Here is the link to join this course:-Deep Learning in Computer Vision.