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Create algorithms that can interpret images and videos to revolutionize healthcare, security, robotics, and more. Learn about computer vision today with edX.

What is computer vision?

Computer vision is a subfield of artificial intelligence and machine learning that focuses on enabling computers to extract meaningful information from visual data, such as images or videos. It involves developing algorithms and techniques to understand, interpret, and analyze visual content, simulating human visual perception.

Computer vision plays a crucial role in numerous applications, including object recognition, image and video analysis, autonomous vehicles, medical imaging, augmented reality, and robotics. One example is facial recognition software on smartphones that allow the owner’s face to operate as a passcode.

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Computer vision course curriculum

Computer vision could be taught as a part of a broader course on machine learning and artificial intelligence. It could be taught as a standalone course or series of classes. Learners who want to gain computer vision skills will likely want to have prior knowledge of machine learning algorithms.

An introductory computer vision course could cover topics such as:

  • Computer vision applications

  • Imaging processing and formation capabilities

  • Using Python, Watson AI, and OpenCV to process images

  • Image classification models

  • Custom image classifiers

Start building the knowledge you need to work in the computer vision and artificial intelligence field with edX. From accelerated boot camps to comprehensive programs that allow you to earn a bachelor’s degree or (for more advanced learners) a master’s degree, there are many different learning formats available to fit your needs. Busy professionals can even take advantage of executive education courses tailored to those in leadership and management positions. Find the right course for you.

Explore computer vision jobs

Computer vision could be one piece of a broader career in machine learning and artificial intelligence, as it can be a useful skill to supplement research. However, some people may find that they prefer to pursue a career that works primarily with computer vision techniques. Whatever path you choose, there are a variety of industries that utilize computer vision skills. Some examples of such jobs could include:

  • Machine learning engineer: Apply machine learning techniques to computer vision problems, such as training deep neural networks for image classification or object detection.

  • Autonomous vehicle engineer: Implement computer vision algorithms and systems for autonomous vehicles, enabling them to perceive and understand the surrounding environment.

  • Medical imaging specialist: Apply computer vision techniques to medical imaging data for tasks such as tumor detection, image segmentation, or diagnostic assistance.

  • Video game developer: Create computer vision-based systems for virtual reality (VR) or augmented reality (AR) games, incorporating object recognition, motion tracking, and gesture-based interactions.

Each of these roles will have different education and skills requirements. For example, you may be able to build relevant skills in a coding boot camp. However, some employers may seek candidates with a degree in computer science, depending on the role. Before deciding on a specific learning path, research the positions you hope to pursue and align your coursework with your career goals.

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