9 Best Online Courses for Computer Vision You Need to Know in 2024

Computer vision is the technology that enables the digital world to interact with the physical world. So if you are looking for the best online courses for computer vision, then give your few minutes to this article. In this article, I have listed the 9 best computer vision online courses.

Computer vision is used for face recognition, Optical Character Recognition, Object Recognition, 3D imaging, and image-guided surgery, etc. Computer vision enables self-driving cars to make sense of their surroundings. There are lots of other applications of computer vision.

The scope of computer vision is growing fast. According to a report, the market for computer vision is expected to increase from US$10.9 billion in 2019 to US$17.4 billion by 2024, at a growing CAGR of 7.8%.

I have filtered these courses on the following criteria-

Criteria-

1. Rating of these Courses.
2. Coverage of Topics.
3. Engaging trainer and Interesting lectures.
4. Number of Students Benefitted.
5. Good Reviews from various aggregators and forums.

So, without further ado, let’s start finding Best Online Courses for Computer Vision.

Best Online Courses for Computer Vision

1. Convolutional Neural Networks– deeplearning.ai

Rating- 4.9/5

Provider- deeplearning.ai

Time to Complete- 20 hours

This course will teach you the key features and concepts that are required to build CNN(convolutional neural network). In this course, you will learn how to apply convolutional networks to visual detection and recognition tasks.

This course is combined with small assessments or questions which makes it easier to follow along. In a nutshell, this course is best to start out in the world of CNN.

Now, let’s see the syllabus of the course-

Syllabus of the Course-

• Foundations of Convolutional Neural Networks
• Deep convolutional models: case studies
• Object detection
• Special applications: Face recognition & Neural style transfer

Extra Benefits-

• You will get Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who have some prior knowledge in Python and Machine Learning.

Interested to Enroll?

If yes, then check out all details here- Convolutional Neural Networks

2. Become a Computer Vision Expert– Udacity

Rating- 4.7/5

Provider- Udacity

Time to Complete- 3 months (If you spend 10-15 hours/week)

This is a Nano-Degree program offered by Udacity. This program will teach you how to write programs for analyzing images, implementing feature extraction, and recognizing objects using deep learning models.

In this program, you will learn from basic image processing to building and customizing convolutional neural networks. This Nano-degree program contains projects such as facial keypoint detection, automatic image captioning, and landmark detection & tracking.

Along with this, you will learn techniques used in self-driving car navigation and drone flight.

There are 3 courses in this Nano Degree Program. Let’s see the details of the courses-

Courses List-

1. Introduction to Computer Vision
2. Advanced Computer Vision and Deep Learning
3. Object Tracking and Localization

Extra Benefits-

• You will get a chance to work on Real-world projects with Industry Experts.
• You will get Technical mentor support.
• Along with this, you will get a personal coach & career services,
• Interview preparations,
• Resume services,
• Github review,
• LinkedIn profile review.

Who Should Enroll?

• Those who have intermediate-level knowledge in Python, statistics, machine learning, and deep learning.
• And those who have worked before with a deep learning framework like TensorFlow, Keras, or PyTorch.

Interested to Enroll?

If yes, then check out all details here- Become a Computer Vision Expert

3. Self-Driving Cars Specialization– University of Toronto

Rating- 4.7/5

Provider- University of Toronto

Time to Complete- 7 months (If you spend 5 hours/week)

This is a specialization program and gives you a deep understanding of state-of-the-art engineering practices used in the self-driving car industry. In this program, you will interact with real data sets from an autonomous vehicle.

You will do hands-on projects using the open-source simulator CARLA. After successfully completing this specialization program, you will be able to build your own self-driving software stack. This specialization program has 4 courses.

Let’s see the courses details-

Courses Details-

1. Introduction to Self-Driving Cars
2. State Estimation and Localization for Self-Driving Cars
3. Visual Perception for Self-Driving Cars
4. Motion Planning for Self-Driving Cars

Extra Benefits-

• You will get a Shareable Certificate and Course Certificates upon completion.
• Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who have prior knowledge in linear algebra, probability, statistics, calculus, physics, control theory, and Python programming.

Interested to Enroll?

If yes, then check out all details here- Self-Driving Cars Specialization

4. Introduction to Computer Vision with Watson and OpenCV– IBM

Rating- 4.4/5

Provider- IBM

Time to Complete- 15 hours

This is a beginner-friendly course and teaches you the fundamental concepts of computer vision. In this course, you will get to know about various applications of computer vision across many industries.

The best part about this course is that it has several labs and exercises. And you will utilize Python, Watson AI, and OpenCV to process images and interact with image classification models.

In this course, you will also build, train, and test your own custom image classifiers. You will perform all practicals on the Cloud. And you will be provided access to a Cloud environment completely free of charge.

After completing this course, you will build your own computer vision web app and deploy it to the Cloud.

Now, let’s see the syllabus of the course-

Syllabus of the Course-

• Introduction to Computer Vision
• Image Classification with IBM Watson
• Custom Classifiers with Watson Visual Recognition
• Image Processing using IBM Watson and Python
• Image Processing using OpenCV and Python
• Project: Building a Web-Based Computer Vision App using IBM Cloud

Extra Benefits-

• You will get a Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who have some prior knowledge in Python.

Interested to Enroll?

If yes, then check out all details here- Introduction to Computer Vision with Watson and OpenCV

5. AWS Computer Vision: Getting Started with GluonCV– AWS

Rating- 4.6/5

Provider- AWS

Time to Complete- 29 hours

This course gives you an overview of Computer Vision, Machine Learning with AWS. In this course, you will learn how to build and train a computer vision model using the Apache MXNet and GluonCV toolkit.

This course tells you about AWS services and frameworks including Amazon Rekognition, Amazon SageMaker, Amazon SageMaker GroundTruth, and Amazon SageMaker Neo, AWS Deep Learning AMIs via Amazon EC2, AWS Deep Learning Containers, and Apache MXNet on AWS.

In the final project, you have to select the appropriate pre-trained GluonCV model, apply that model to your dataset, and visualize the output of your GluonCV model.

Now, let’s see the syllabus of the course-

Syllabus of the Course-

• Introduction to Computer Vision
• Machine Learning on AWS
• Using GluonCV Models
• Gluon Fundamentals
• Gluon Fundamentals Continued
• Final Project

Extra Benefits-

• You will get a Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who are familiar with Python.

Interested to Enroll?

If yes, then check out all details here- AWS Computer Vision: Getting Started with GluonCV

6. Python for Computer Vision with OpenCV and Deep Learning– Udemy

Rating- 4.6/5

Provider- Jose Portilla

Time to Complete- 14 hours

This course teaches computer vision by using Python and the OpenCV library. At the beginning of the course, you will learn about numerical processing with the NumPy library and how to open and manipulate images with NumPy.

This course teaches you how to process images and apply a variety of effects, including color mappings, blending, thresholds, gradients, and more. You will also learn about face detection and object tracking.

Extra Benefits-

• You will get a Certificate of completion.
• And you will get Full lifetime access to course materials.

Who Should Enroll?

• Those who have intermediate level Python knowledge.

Interested to Enroll?

If yes, then check out all details here- Python for Computer Vision with OpenCV and Deep Learning

7. Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs– Udemy

Rating– 4.5/5

Provider- SuperDataScience Team

Time to Complete- 11 hours

This course will help you to understand the theory behind Computer Vision. In this course, you will learn Facial Recognition with OpenCV, object detection with SSD, and Image creation with GAN. This course also teaches you about artificial neural networks and convolutional neural networks.

Extra Benefits-

• You will get a Certificate of completion.
• And you will get Full lifetime access to course materials.

Who Should Enroll?

• Those who have basic python programming knowledge and high-school level math.

Interested to Enroll?

If yes, then check out all details here- Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs

8. Image Understanding with TensorFlow on GCP– Google Cloud Training

Rating- 4.6/5

Provider- Google Cloud

Time to Complete- 12 hours

This course will teach you different strategies for building an image classifier using convolutional neural networks. In this course, you will learn how to improve the model’s accuracy with augmentation, feature extraction, and fine-tuning hyperparameters.

You will also practice building and optimizing your own image classification models with a variety of public datasets. Now, let’s see the syllabus of the course-

Syllabus of the Course-

1. Welcome to Image Understanding with TensorFlow on GCP
2. Linear and DNN Models
3. Convolutional Neural Networks (CNNs)
4. Dealing with Data Scarcity
5. Going Deeper Faster
6. Pre-built ML Models for Image Classification

Extra Benefits-

• You will get a Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who are familiar with SQL, Python, and TensorFlow.

Interested to Enroll?

If yes, then check out all details here- Image Understanding with TensorFlow on GCP

9. Python Project: pillow, tesseract, and opencv– University of Michigan

Rating- 4.0/5

Provider- University of Michigan

Time to Complete- 20 hours

This course provides an introduction to the third-party APIs, manipulates images using the Python imaging library, and applies optical character recognition to images to identify text, faces using the OpenCV library.

In this course, you will work with three different libraries available for Python 3 to create a real-world data-analysis project.

Now, let’s see the syllabus of the course-

Syllabus of the Course-

1. The Python Imaging Library
2. Tesseract and Optical Character Recognition
3. Computer Vision with OpenCV

Extra Benefits-

• You will get a Course Certificates upon completion.
• Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.

Who Should Enroll?

• Those who are comfortable in Python 3.

Interested to Enroll?

If yes, then check out all details here- Python Project: pillow, tesseract, and opencv

And that’s all…So, these are the 9 Best Online Courses for Computer Vision. Now, it’s time to wrap up.

Conclusion

I hope these 9 Best Online Courses for Computer Vision will help you to learn Computer Vision. My aim is to provide you the best resources for Learning. If you have any doubt or questions, feel free to ask me in the comment section.

Tell me in the comment section, which course you like.

All the Best!

Happy Learning!

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