Computer Vision is the branch of Computer Science—particularly Machine Learning and AI—that has applications in many industries such as self-driving cars, robotics, augmented reality, face detection in law-enforcement agencies, and more. Essentially, it’s a robot analogue of human vision in which information about the environment is received by one or more video cameras and processed by a computer.

Computer Vision solves a lot of problems, making it important to learn. Some of its uses include advances in health technologies. Computer Vision algorithms can help automate tasks such as detecting cancerous moles in skin images or finding symptoms in x-ray and MRI scans.

Thanks to a need for quality inspection in vision-guided robotic systems, the market for Computer Vision is anticipated to rise to $17.4 billion by 2024. To reap the benefits of this in-demand field, learners can enjoy opportunities as Computer Vision Engineers, Computer Vision Software Engineers, Applied Research Scientists, Computer Vision Testing Engineers, Deep Learning Engineer, Computer Vision Data Scientist, and more.

Computer Vision courses offered through Coursera equip learners with knowledge in how computers see and interpret the world as humans do; core concepts of Computer Vision and human vision capabilities; key application areas of Computer Vision and Digital Image Processing; Machine Learning and AI basics; and more.

Lessons on Computer Vision are taught by Data Scientists, Software Engineers, and other specialists, and are administered via video lectures, readings, quizzes, hands-on projects, and more.