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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 s