7 Best Free Computer Vision Courses You Must Know in 2025

Computer vision is used for face recognition, Optical Character Recognition, Object Recognition, 3D imaging, and image-guided surgery, etc. So, If you are looking for Best Free Computer Vision Courses, this article is for you. In this article, you will find the 7 Best Free Computer Vision Courses.

Now without further ado, let’s get started-

Best Free Computer Vision Courses

1. Introduction to Computer Vision– Udacity

Time to Complete–	4 Months
Rating-	NA

This is a completely FREE Course to learn Computer Vision. This is a very detailed course. As a free course, I found this course is the most in-depth course.

The course starts with the computer vision basics and then you will learn advanced concepts of computer vision such as fundamentals of image formation, camera imaging geometry, feature detection and matching, multiview geometry including stereo, motion estimation, tracking, and classification.

You will also develop basic methods for applications that include finding known models in images, depth recovery from the stereo, camera calibration, image stabilization, automated alignment (e.g. panoramas), tracking, and action recognition.

This course will help you to develop the intuitions and mathematics of the methods and understand the difference between theory and practice in the problem sets.

You Should Enroll If-

• You have a good working knowledge of Matlab and/or Python with NumPy.

Interested to Enroll?

If yes, then check out the course details here- Introduction to Computer Vision

2. Computer Vision Basics– Coursera

Time to Complete–	13 hours
Rating-	4.2/5

This is a Free to Audit course on Coursera. That means you can access the course material free of cost but for the certificate, you have to pay.

To audit the course for free, click on the “Enroll for Free” button and Coursera will ask for two options one is Purchase Course and another one is Audit only. Choose the “Audit only” option and you will be redirected to the course material for free.

The course has a 4-week study plan. In week 1, you will learn the basics of computer vision and the applications of computer vision. In the next week, you will understand color theory, light sources, digital cameras, etc.

The third week will cover a three-level paradigm and low, mid, and high-level vision. The last week is all about mathematical concepts of computer vision such as linear algebra, calculus, probability, etc.

You will get a free license to install MATLAB for the duration of the course available from MathWorks.

You Should Enroll If-

• You have basic programming skills and are familiar with basic linear algebra, calculus & probability, and 3D coordinate systems & transformations.

Interested to Enroll?

If yes, then check out the course details here- Computer Vision Basics

3. Intel® Edge AI Fundamentals with OpenVINO™– Udacity

Time to Complete–	1 Month
Rating-	NA

This is another Free Course to understand the Intel® Distribution of OpenVINO™ Toolkit. This course has 5 lessons. In the first lesson, you will learn what is AI at the Edge and the applications of AI at the Edge. Next, you will learn the OpenVINO™ Toolkit, types of Computer Vision Models, Case Studies in Computer Vision, Available Pre-Trained Models in OpenVINO™, etc. This lesson also has exercises on computer vision.

The next lesson is all about the Model Optimizer and Optimization Techniques. You will also learn how to use the Model Optimizer with TensorFlow Models.

The last two lessons will cover the Inference Engine, how to use the Inference Engine with an IR, OpenCV Basics, how to handle Input Streams, MQTT, etc.

This course is combined with various exercises and practices.

You Should Enroll If-

• You have basic Python experience and basic familiarity with computer vision and AI model creation.

Interested to Enroll?

If yes, then check out the course details here- Intel® Edge AI Fundamentals with OpenVINO™

4. Advanced Computer Vision with TensorFlow– Coursera

Time to Complete–	29 hours
Rating-	4.8/5

This is a Free to Audit course. To access the course material for Free, press-> Enroll for Free and then press-> Audit the Course.

This is a 4-week study plan. In week 1, you will learn the basics of computer vision, transfer learning, advanced transfer learning, object localization, and detection.

The next week, you will learn object detection, sliding window, R-CNN, Fast R-CNN, how to implement simple object detection in TensorFlow, etc.

In the third week, you will understand image segmentation, FCN architecture, U-Net, etc. And the last week will cover why interpretation matters, saliency, GradCAM, ZFNet, etc.

The lab exercises are locked in the free-to-access mode.

You Should Enroll If-

• You have working experience with Python, TF/Keras/PyTorch framework, and basic knowledge of deep learning, calculus, linear algebra, and stats.

Interested to Enroll?

If yes, then check out the course details here- Advanced Computer Vision with TensorFlow

5. Computer Vision– Kaggle

Time to Complete–	4 hours
Rating-	NA

This Free Course is available on Kaggle. In this course, you will understand the fundamental ideas of computer vision and use modern deep-learning networks to build an image classifier with Keras.

You will also design your custom convnet with reusable blocks and learn the fundamental ideas behind visual feature extraction and Transfer learning.

You Should Enroll If-

• You have basic knowledge of Deep Learning.

Interested to Enroll?

If yes, then check out the course details here- Computer Vision

6. Introduction to Computer Vision and Image Processing– Coursera

Time to Complete–	21 hours
Rating-	4.4/5

This is another Free to Audit Coursera course. To access the course material for Free, press-> Enroll for Free and then press-> Audit the Course.

This is a detailed course and has a 6-week study plan. The course begins with computer vision basics and its applications. Next, you will learn image processing with Pillow and OpenCV. You will learn basic image manipulation using OpenCV, pixel transformations, histograms, and intensity transformations.

In the third week, you will learn image classification with KNN, linear classifiers, logistic regression training, support vector machines, and image classification with SVM and CV studio.

The fourth week will cover deep learning algorithms such as neural networks, CNN, etc. The last two weeks are all about object detection with Haar Cascade Classifier and assignments.

You Should Enroll If-

• You have some knowledge of the Python programming language and high school math.

Interested to Enroll?

If yes, then check out the course details here- Introduction to Computer Vision and Image Processing

7. Computer Vision with OpenCV Python | Official OpenCV Course– Udemy

Time to Complete–	1hr 59min
Rating-	4.9/5

This is a completely free course to learn OpenCV for Computer Vision. In this course, there are 15 sections. You will learn Image, Image manipulation, Image Annotation using OpenCV, Arithmetic Operations on Images, and Bitwise Operations on Images.

You will also learn Image Filtering in OpenCV, Image Features, Image Alignment, Object Tracking, Face Detection, Object Detection, and Human Pose Estimation using Deep Learning.

You Should Enroll If-

• You have basic knowledge of Python.

Interested to Enroll?

If yes, then check out the course details here- Computer Vision with OpenCV Python | Official OpenCV Course

Summary of Best Free Computer Vision Courses

S/N	Course Name	Rating	Time to Complete
1.	Introduction to Computer Vision– Udacity	NA	4 Months
2.	Computer Vision Basics– Coursera	4.2/5	13 hours
3.	Intel® Edge AI Fundamentals with OpenVINO™– Udacity	NA	1 Month
4.	Advanced Computer Vision with TensorFlow– Coursera	4.8/5	29 hours
5.	Computer Vision– Kaggle	NA	4 hours
6.	Introduction to Computer Vision and Image Processing– Coursera	4.4/5	21 hours
7.	Computer Vision with OpenCV Python | Official OpenCV Course– Udemy	4.9/5	1hr 59min

And here the list ends. I hope these Best Free Computer Vision Courses will help you to learn Computer Vision. I would suggest you bookmark this article for future referrals. Now it’s time to wrap up.

Conclusion

In this article, I tried to cover all the Best Free Computer Vision Courses. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

Thank YOU!

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Though of the Day…

‘ Anyone who stops learning is old, whether at twenty or eighty. Anyone who keeps learning stays young.

– Henry Ford