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Martin Barrett
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Best Coursera Computer Vision Courses

Best Coursera Computer Vision Courses You Must Know In 2023

Computer technology is coming in leaps and bounds and now they have reached the point where an AI (Artificial Intelligence) can gather data from a picture or a video. This field is known as computer vision, and it is a fast-expanding subset of computer science.

If you do have prior experience in computer science and you want to gain employment in this field, then you might want to try one of the hundreds of online computer vision courses that Coursera offers. Coursera is an online learning platform that helps you assimilate your learning into a busy work life.

So, what are the best computer vision courses that Coursera has to offer in computer vision? Which ones are aimed at beginners and which are aimed at professionals? Well, we have scoured Coursera for some of the best Coursera computer vision courses, so check them out below.

Best Coursera Computer Vision Courses

1. First Principles Of Computer Vision Specialization

This advanced computer vision course helps you get to grips with computer vision and image processing as well as facial recognition works and the areas in which you might apply it. This will also help you to capture the 3D aspect of a shape from a 2D image.

This is a flexible learning course, which means that you can learn computer vision at whatever pace you like. This is great if you are trying to build a course schedule around your busy work life. This is also a good foundational course for further deep learning, as it unpacks some of the basic ideas.

2. Introduction To Computer Vision

If you want a course that lays out the basic terms of computer vision, then this is the course for you. This will teach you how to combine images together to get a larger picture. It will also explore facial detection algorithms and how to extract 3D objects from 2D images.

This course is 8 hours long, although it will require an intermediate knowledge of how computer vision works. This comes with a flexible timetable that will allow you to plan your lessons as you feel necessary.

3. Computer Vision for Engineering and Science Specialization

This course will teach you the computer vision basics and how they are applied in all sorts of situations, from invasive surgery to identifying suspects in a crime. You will also learn about tracking movement in video and multiple objects at any one time.

This is a very long course and will take you around 3 months to complete. It is ideal as a supplementary learning program to go alongside a more academic learning structure. This course requires an intermediate knowledge of computer vision and engineering before you enroll.


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4. Object Tracking and Motion Detection with Computer Vision

This course specializes in tracking objects in video with computer vision technology. You will be put in various roles, such as engineers tasked with tracking certain cars in video footage.

This course will also teach you how to use motion detection in old footage to predict motion in other videos.

This course offers flexible learning, which is great if you are looking for something that you can incorporate into your busy schedule. This is the third part of a wider course on engineering and computer specialization.

5. Advanced Computer Vision with TensorFlow

This is a free course that covers some of the basic principles of object detection, ranging from image localization to image segmentation. This is aimed at future software engineers and machine learning engineers who want to use the program TensorFlow for image detection.

This is the final part of a 4-part course on Advanced Techniques Specialization, so you’ll need an intermediate to advanced level of knowledge to get to grips with this section. This is online learning, so you won’t have to go through the hassle of having to turn up for class.

6. Machine Learning For Computer Vision

When it comes to classifying images and image detection, this is a great course for you to try. This will help you to prepare your entire machine-learning workflow and how you can apply computer vision to classifying street signs and finding imperfections in image software.

This course will provide you with free use of MATLAB software, which is the go-to learning platform for anyone working in engineering or computer science. This course only takes you 12 hours to complete and is part of a larger course on machine learning.

7. Introduction To Computer Vision And Image Processing

When it comes to the real-world application of computer vision technology, this is a great place to start. This will explain how computer vision is used in things such as self-driving cars and certain surgeries.

This is a great course for beginners and will really map out how the computer vision sector is helping in a variety of other sectors, from automobiles to medicine. This is also great for anyone who is looking to get into robotics or augmented reality.

Coursera Computer Vision Courses

8. Computer Vision Basics

This course will help you identify certain basics of computer vision, including color, light, and image formation, and how it factors into machine-learned computer vision.

This also acts as a refresher course for those that might need to brush up on computational mathematics.

This will gain you experience in writing programming, offering you course materials such as videos, tutorials, class discussions, project work, and hands-on exercises. This will also help you work on 3D modeling and 2D graphics work.

9. Self-driving Cars

This industry represents a new horizon in automated technology. If you want a part in this burgeoning sector, then doing this course will help you get ahead of the competition. This will help you with implementing methods of object detection, both moving and stationery.

This is a great course to supplement your existing machine learning, helping you to develop self-driving machine programs and other basic programming skills that will make you more employable. This course will take around 7 months to complete, although the course is flexible.

10. Computer Vision With Embedded Machine Learning

This is another great course for anyone with no prior knowledge of machine learning who wants to either expand their existing computer science knowledge or just wants to understand how some of the basic image detection systems work.

This will help you to understand the knowledge classification system that is used by machine detection software. This course will take you around 31 hours to complete, with a flexible working schedule and a completely online learning platform.

11. Deep Learning Applications For Computer Vision

These computer vision applications aim to explain what is going on in computer vision software and what tasks can be completed using computer vision. This will help you apply this technology to real-world scenarios such as image detection.

This will give you the tools to perform computer vision tasks. It can be completed in just over 22 hours and comes with a certificate of completion. This is an intermediate-level course and requires basic calculus and linear algebra to enroll.

12. Introduction To Computer Vision With TensorFlow

This Google course is perfect for condensing all the basic concepts of computer vision into 1 hour. This comes with website-only content and videos that will help you to understand some of the core tenets of this subject.

The great thing about this course is that you won’t have to download any course materials, it all happens through the Google website. This course is only available in English, but you will get a shareable certificate once you have completed it.


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13. Visual Perception For Self-Driving Cars

This is another course for anyone who is looking for a career in the software behind self-driving cars. This will help you to achieve camera calibration for motion detection, as well as image segmentation of roadways and other designated driving paths.

This is an advanced course and can only be enrolled in by students who have completed the computer vision and deep learning standard courses. This course takes around 31 hours to complete, which makes it ideal for anyone who does not want to study for longer than a month or two.

14. Robotics

Computer vision is a huge part of robotics, with drones having to rely on machine learning to detect moving objects and chart certain trajectories. This will help you to learn about how robots understand their environment and how they overcome physical obstacles.

This course can be studied over a period of 7 months, with a suggested working pace of around 5 hours per week.

This is another beginner-level course, so you won’t have to have any prior knowledge of robotics, although you’ll need to study this in addition to a university degree to gain employment.

Coursera Computer Vision Courses

15. Camera And Imaging

This course examines the history of imaging as well as camerawork and how the two work together. This studies the history of imaging, which spans decades, bringing you up to the latest innovations in camera imaging technology.

This covers things like developing binary images that will help you to create a full image detection system. It is the first course out of 5 and will only take you 17 hours to complete. This course has a certificate at the end that you can share as part of your CV.

16. AI For Medical Diagnosis

AI is being used more and more in the medical field, helping to diagnose patients more accurately and recommend better treatments. This course will give you all the information that you need to understand modern medical innovations using AI.

This is part 3 in a 3-part course on AI In Medicine Specialization. This is an intermediate-level course, which means that you will need a basic understanding of computer vision concepts. AI For Medical diagnosis is available through a flexible online working program.

17. Build a computer vision app with Azure Cognitive Services

This next course is a free one that is available from Google, and it gives you all the information that you need to build a machine learning app that is available through Microsoft Azure. This will provide you with a free Microsoft Azure account to help with your learning.

This course does not need you to download any information or course documents, as it is all available from the website. This course comes in a split-screen video where your instructor will go through the course with you. This is a flexible course, although it will only take 1 hour to complete.

Frequently Asked Questions

Q: Why Would A Coursera Course Be Suitable For Me?

A: If you are leading a busy life, either personally or in your work life, then the best online courses might be the best method for learning for you. Many of these online training courses have flexible learning structures and deadlines, meaning you can complete the course as and when you like.

Q: What Jobs Will Computer Vision Qualify Me For?

A: Computer vision is applicable in all sorts of sectors, including machine learning, robotics, self-driving cars, image detection, and certain sectors of crime prevention.

Q: Will Employers Accept Coursera Course Certificates?

A: Not all employers accept Coursera certificates as they are not officially accredited free online courses. However, you can always check with your employer first to see if they will be willing to accept your Coursera certificate before you have applied for the course.

Q: How Much Will I Have To Pay For A Coursera Course?

A: There are various pricing models for each course. If you choose a Coursera Plus subscription, then that will cost you around $399 per year. There are also full degrees that are worth around $9,000 per year.

You can also pick specialization courses and professional certificates that will cost around $39.99 per month.


Coursera is a great place for anyone to start learning computer vision. You can even go on a course knowing nothing about the subject whatsoever. Online courses are great to supplement your learning either before or during a degree course.

Make sure you are aware of the pricing structure of your Coursera course, as they can get a little expensive.

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