Computer vision is the field of study that enables computers to see and understand the visual world. It is one of the most exciting and rapidly evolving areas of artificial intelligence, with applications ranging from face recognition and biometrics to self-driving cars and augmented reality. In this course, you will learn the fundamental concepts and techniques of computer vision, as well as how to apply them to real-world problems.

This course provides a comprehensive introduction to the field of computer vision. It covers the fundamental concepts of image representation and processing, image features and descriptors, image classification and object recognition, motion analysis and tracking, and 3D computer vision.

The course is structured into six modules, each covering a major topic of computer vision. Each module consists of video lectures, quizzes, and assignments. You will not need to write any code in this course, as you will use interactive tools and platforms that allow you to experiment with computer vision algorithms. You will also have access to a rich set of resources, such as readings, code examples, and datasets.

By the end of this course, you will have a solid foundation in computer vision. You will also gain a deeper appreciation of the power and potential of computer vision, as well as its ethical implications and limitations. Whether you want to pursue a career in computer vision, enhance your existing skills, or simply satisfy your curiosity, this course will help you achieve your learning goals.

Who this course is for:

• Beginners in computer vision
• Students and professionals in computer science, engineering, and related fields
• Anyone who is interested in learning how computers can see