The 10 best Computer Vision courses in 2026

Introduction to Computer Vision guides learners through the essential algorithms and methods to help computers 'see' and interpret visual data. You will first learn the core concepts and techniques that have been traditionally used to analyze images. Then, you will learn modern deep learning methods, such as neural networks and specific models designed for image recognition, and how it can be used to perform more complex tasks like object detection and image segmentation. Additionally, you will learn the creation and impact of AI-generated images and videos, exploring the ethical consideration

In the first course of the Computer Vision for Engineering and Science specialization, you’ll be introduced to computer vision. You'll learn and use the most common algorithms for feature detection, extraction, and matching to align satellite images and stitch images together to create a single image of a larger scene. Features are used in applications like motion estimation, object tracking, and machine learning. You’ll use features to estimate geometric transformations between images and perform image registration. Registration is important whenever you need to compare images of the same s

This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this course, you will explore the fascinating world of computer vision and artificial intelligence through the NVIDIA Jetson platform. By working through various modules, you'll gain a strong understanding of how to set up and optimize Jetson for AI tasks, with hands-on projects and practical applications of Jetson's capabilities. The course covers everything from bas

By the end of this course, learners will be able to analyze video data, apply color models, implement image preprocessing techniques, and build object detection and tracking solutions using OpenCV and Python. They will gain the ability to process real-time and recorded video streams, extract meaningful visual features, and apply motion analysis algorithms to solve practical computer vision problems. This course benefits learners by providing a structured, hands-on pathway from foundational concepts to advanced video analytics techniques. Learners will develop industry-relevant skills in image

This course covers the fundamentals of imaging – the creation of an image that is ready for consumption or processing by a human or a machine. Imaging has a long history, spanning several centuries. But the advances made in the last three decades have revolutionized the camera and dramatically improved the robustness and accuracy of computer vision systems. We describe the fundamentals of imaging, as well as recent innovations in imaging that have had a profound impact on computer vision. This course starts with examining how an image is formed using a lens camera. We explore the optical char

In this course, you’ll start with a review of the mechanisms behind anthropogenic climate change and its impact on global temperatures and weather patterns. You will work through two case studies, one using time series analysis for wind power forecasting and another using computer vision for biodiversity monitoring. Both case studies are examples of where AI techniques can be part of the solution when it comes to the mitigation of and adaptation to climate change.

With Amazon Kinesis Video Streams, you can build media streaming applications for Internet of Things (IoT) video devices and real-time computer vision machine learning (ML) applications. In this course, you will learn the benefits and technical concepts of Kinesis Video Streams. If you are new to the service, you will learn how to start using Kinesis Video Streams through a demonstration using the AWS Management Console. You will learn about the native architecture and how the built-in features can help you simplify image extraction through APIs or automated image extraction from metadata tag

Five courses on neural networks, CNNs, sequence models, and ML strategy from DeepLearning.AI.

Build and train neural networks with TensorFlow for vision, NLP, and time series.

Free, top-down deep learning course — build state-of-the-art models from lesson one.