This article will cover the best free and paid online computer vision courses for beginners and those experienced in coding but new to Computer Vision.

Computer vision technology is highly popular, and becoming a Computer Vision Engineer is a promising career option for beginners as well as for experienced developers.

We have put together resources to learn about Computer Vision in well-structured online courses. Therefore, and to help you evaluate which course to attend, we evaluated the most popular courses and created a list.



The 6 best online Computer Vision courses:
  • Course #1: Introduction to Computer Vision and Image Processing by IBM
  • Course #2: Python for Computer Vision with OpenCV and Deep Learning
  • Course #3: Python Project: Pillow, Tesseract, and OpenCV Course
  • Course #4: Free Introduction to Computer Vision Course
  • Course #5: Computer Vision Basics
  • Course #6: Become a Computer Vision Expert – A Nanodegree Program

1. Introduction to Computer Vision and Image Processing

An online course offered by IBM on Coursera.

Description: This beginner-friendly course will give you an understanding of Computer Vision and its various applications across many industries, such as autonomous cars, robotics, and face recognition. The free lessons include hands-on exercises to upload, train, and test your own custom image classifier and detection models. You will create a simple computer vision web app and deploy it to the Cloud. The course does not require prior knowledge about Machine Learning or Computer Vision. Nevertheless, some prior knowledge of the Python programming language is required.

Our Review: The course is a perfect starter guide for those interested in Computer Vision; it is clear, well-made, and interesting. There are plenty of examples and a variety of applications. Because the course includes IBM Cloud and 90% of the course are lab assignments, while this is very engaging, it can lead to difficulties if the labs are unstable or non-responsive. While the course title is about OpenCV, it is very specific to using IBMs Product, the Watson Visual Recogniser, and explains it well. However, the math behind Computer Vision and using OpenCV are not covered in-depth, but it still is a great course for beginners.

The online computer vision course covers applications like Object Detection
This Computer Vision course covers applications like Object Detection

2. Python for Computer Vision with OpenCV and Deep Learning

An online course offered on Udemy.

Description: This online course consists of 10 sections and focuses on learning how to use the Python programming language for Computer Vision. Therefore, it includes an introduction to Python and the OpenCV library to perform Computer Vision tasks on images and videos. Furthermore, the course covers numerical processing and image manipulation using the NumPy library before moving to image processing with OpenCV. Next, you will learn about performing face detection and object tracking on video streams from a webcam. Finally, the course covers the latest Deep Learning Networks such as YOLO (You Only Look Once, see an example below). The course requires you to have a clear understanding of Python and Ubuntu.

Our Review: The course is very well structured and easy to follow. The subject is explained very well and practical, one of the best courses on Computer Vision we found that will help to give starters a good understanding of OpenCV. However, as the course advances and gets more in-depth, we wished there were more explanations regarding the coding. The assignments are not much of a challenge, as everything except for the syntax is provided to solve the problem, even the algorithm, and parameters to use. This makes the examples too simple compared to real image processing issues that Machine Learning and Deep Learning try to solve.

  • Type: Paid (13 USD)
  • Level: Intermediate
  • Duration: 14 hours
  • Find it here
The computer vision course covers Object Detection with YOLO
The course covers state-of-the-art Computer Vision with Deep Learning Networks such as YOLO

3. Python Project: Pillow, Tesseract, and OpenCV

An online course offered by the University of Michigan on Coursera.

Description: This online course by the University of Michigan is an introduction to three different libraries available for Python 3 to create a real-world computer vision project. Therefore, the course includes free lessons about using third-party APIs for face recognition with the help of the popular OpenCV library, performing optical character recognition (OCR, see an example below), and image manipulation through Python.

Our Review: The course gives great insights into how to approach a new library which is an essential skill every Computer Vision Engineer must have. We liked that the course is close to a real-world-type programming project that offers a serious challenge instead of a theoretical assignment. However, this makes the course significantly more difficult than others, and having some programming experience is highly recommended. Sometimes, the course felt a bit rushed, and because of the limited time, the lections only give a high-level overview of PIL, Tesseract, and OpenCV.

  • Type: Free
  • Level: Intermediate
  • Duration: 20 hours
  • Find it here
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