9 Best Online Computer Vision Courses & Certification of 2023

It is quite difficult for students to find the best way to suit their needs with many Computer Vision courses. We are often asked by students whether there is a standard course of Computer Vision that fits every case. YES is the reply. You can participate in the following popular courses. Registering for the right course will make a major difference in your career growth. The four best Computer Vision courses & classes of 2023 have been chosen by hand in this article.

Our focus is on highlighting their respective categories as the best and most popular courses.

You can select the one which best fits your needs depending on your use case.

Let us look at the best Computer Vision courses available on the market, however.

1. Convolutional Neural Networks Course by deeplearning.ai (Coursera)

Duration: 4 weeks, 4 to 5 hours per week

Rating: 4.8 out of 5

The program discusses the key features and principles required for creating convolutionary neural networks and implementing them on image data. Learn to use the visual-detection and recognition-tasks networks and use the translation of neural styles to create content. You are able to provide knowledge and work on the related projects upon completion of your class.

Key Highlights:

• The tutorials direct you through all the topics needed to properly handle the instruments used for the lessons.
• Teachers provide tips, advice, and best debugging practices and clean code writing.
• Explanations and instructions are given step by step to better understand the concepts.
• Take a chance to focus on assignments and apply class-based strategies.
• The course is divided into parts with small assessments or questions that encourage follow-up.
• Explore a lot of new and interesting subjects with the instructor’s constant support.
• Finish all the evaluations and exercises to obtain the certificate of completion.

You can Sign up Here 

2. Become a Computer Vision Expert – Nanodegree Program by Nvidia (Udacity)

Duration: 3 months, 10 to 15 hours per week

Rating: 4.5 out of 5

Computer vision is one of the most demanding skills in today’s industries, plays a critical role in robotics and automation. You can start writing image processing programs, execute feature extraction and detect objects with profound learning model in this nanographic stage. Therefore, it’s a clever move to have this degree under your belt if you have previous experience with Python, statistics , machine learning and deep learning.

Key Highlights:

• The related projects, such as facial keypoint detection, automatic image captions and landmark detection and tracking, follow each segment.
• You can learn at your own pace thanks to the versatile courses layout.
• Get help with the preparation of interviews, resume services, coaching and other matters.
• Get to know techniques for self-driving and drone flight navigation.
• To create an application, merge CNN and RNN networks.

You can Sign up Here

3. Introduction to Computer Vision with Watson and OpenCV by IBM (Coursera)

Duration: 15 hours

Rating: 4.5 out of 5

This course, developed by IBM professional professors, gives you all the resources and skills you need to know about computer vision. Taking this course will help you learn basic machine vision concepts so you can see how they are used in various industries, such as self driving vehicles, validated learning, robotics, face detection in law enforcement, etc. During the course, if you have any questions about the course content or are not able to understand the concepts during the course, you will be able to communicate with your teachers. You get a certificate of completion which can be shared with employers after the course is successfully completed.

Key Highlights:

• A hands-on course with several labs and exercises to understand and learn the basic and simple computer vision concept.
• Learn how to use Python, Watson AI, OpenCV for image processing and image classification models.
• Learn how to build, train, and test in visual recognition, your own classifier for custom images and train your classifiers to classify dog images into different breeds.
• Get free access to a cloud environment that lets you create and place your own computer vision web app in the cloud.

You can Sign up Here

4. Python for Computer vision with OpenCV and Deep Learning (Udemy)

Duration: 14 hours

Rating: 4.5 out of 5

This course is one of the leading contenders to learn how computer vision using Python. Begin by learning how to process numerically and by manipulating images with the NumPy library. After exploring the OpenCV library, processing images and applying a variety of effects such as color mapping, thresholds, gradients and more. Complete the training by learning several complicated concepts, coming to grips with the latest trends and discussing.

Key Highlighted:

• This is an intermediate level course and anyone with prior experience in Python can take this course.
• Develop OpenCV color histograms and draw shapes on videos and pictures.
• Execute face detection, matching features, tracking objects and more
• Work on a personalized deep learning network, optical flow, and WaterShed algorithm.
• 92 Lectures + 4 Articles + 3 Downloadable Ressources + Lifetime access
• Accessible on e-learning website Udemy at an affordable price.

You can Sign up Here 

5. Deep Learning and Computer Vision A-Z: OpenCV, SSD & GANs (Udemy)

Duration: 11 hours

Rating: 4.4 out of 5

This qualification will help you break into the world of artificial intelligence and build amazing apps by leveraging the latest technology. Explore methods, methodologies and fundamental principles until they are implemented in practice. Awareness of high school mathematics and basic python is enough to be part of this tutorial. With more than 20,000 students and stellar ratings, this program is a favorite of the crowd.

Key Highlights:

• Have the most effective computer vision models in the toolbox.
• OpenCV Master, facial recognition and object detection.
• The professor is a renowned specialist in this area and discusses the concepts clearly and at a fast pace.
• A wide range of examples helps you get a better understanding of the issues.
• Understand the theory behind the themes and create powerful applications.
• 78 Lectures + 7 Papers + 5 Accessible resources + Full life access

You can Sign up Here 

6. Deep Learning: Advanced Computer Vision (Udemy)

Duration: 7 hours

Rating: 4.7 out of 5

If you’re staying in the loop with the news of developments in technology then I’m sure you’ve learned about how computer vision is hitting new heights. If you have the knowledge to build, train and use a CNN as well as a thorough knowledge of python then this course can come in handy to help you start your career in this area. Learn how to create an object detection system for classifying images, locating the object and predicting its label. Function with state-of-the-art SSD algorithm which will help you accomplish the goal more efficiently and accurately.

Key Highlights:

• From the very beginning, all the topics are covered including the setup of the necessary tools.
• A variety of exercises covering the concepts to check your grasp and to overcome your queries.
• Every other topic is dealt with in an elaborate way, with appropriate examples and demonstrations.
• All code used in the program is downloadable from the instructor’s GitHub.
• 67 Lectures + Access for lifetime.
• Accessible on e-learning platform Udemy at affordable prices.

You can Sign up Here

7. Python Project: Pillow, Tesseract, OpenCV by University of Michigan (Coursera)

Duration: Self-paced

Rating: 4.5 out of 5

The University of Michigan is designing this intermediate-level program to gain a strong footing in the computer vision field. Get an introduction to third party APIs, using the Python image library to manipulate images, apply optical character recognition to images to recognize text, faces using the OpenCV library. You will have the experience of working with three different libraries to create a real-world data science project by the end of the voyage.

Key Highlights:

• Work with the image library, and crop, resize, recolor and overlay text.
• The complete set of lectures is broken into appropriate sections that make it easy for the students to follow.
• The tutor describes all the notions in a clear but succinct way.
• Identify and control the faces in photographs and the crop in contact sheets.
• Pass the graded tests to get the certification and take the opportunity to complete the project.
• You can take the classes according to your convenience, with flexible deadlines.

You can Sign up Here

8. Computer Vision Course by Microsoft (edX)

Duration: 1 course, 4 weeks  per course, 3 to 4 hours per week

Rating: 4.5 out of 5

Using Microsoft Cognitive Toolkit and OpenCV to segment images into meaningful parts, you will explore interesting topics such as image analysis techniques in this hands-on certification. Understand the evolution from the classical to the deep learning techniques in this area. You will have the confidence to take on projects in relevant areas by the end of the lectures, as well as to take your skills a bit higher.

Key Highlights:

• Working knowledge of the fundamentals of python, AI, and deep learning is required.
• Apply Transfer Learning to increase ResNet18 to a Fully Convolutionary Semantic Segmentation Network.
• Use the OpenCV library to implement classical image analysis algorithms.
• The real-world examples make the lectures much clearer and more interesting.
• Cover topics such as edge detection, watershed, inter alia distance transformation.
• A lot of assignments to put the concepts covered in the lectures into practice.
• The course material can be accessed free of charge, and an additional amount can be added to the certification.

You can Sign up Here 

9. Free Computer Vision Course by Georgia Tech (Udacity)

Duration: 4 months

Rating: 4.5 out of 5

This Georgia Tech program is one of the top contenders among this field’s e-learning options. Starting from the fundamentals of image formation, geometry of camera imaging, feature detection and matching, estimation of motion before moving on to practical classes. You will develop basic methods for applications in the hands-on sessions which include finding known models in images, stereo depth recovery, calibration, stabilization, automated alignment, and tracking. This certification does not let you down, with a focus on every important aspect of the topic.

Key Highlights:

• Develop mathematics and intuitions of the methods covered in the lectures.
• The problem sets discuss about the discrepancy between theory and reality.
• Test the interactive quizzes to gauge your understanding of the concepts.
• Self-paced lessons allow you to study as you wish.
• Implement the lecture concepts, and enhance your resume.
• Join the support community for the students, interact with your peers, and clarify your doubts.
• Full research materials and videos are free to download.

You can Sign up Here 

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Wrapping Up

That’s the list of 9 Best Computer Vision Courses & Classes of 2023 with high-quality content. They are popular and loved by many machine learning students. Between these courses, you are sure to find what you need to learn to continue your path of the machine learning.