Applied Artificial Intelligence: Computer Vision and Image Analysis

This course is part the Advanced and Applied AI On Microsoft Azure ExpertTrack. It will help you to develop AI and machine-learning skills, and prepare you for the relevant Microsoft microcredentials. We can see meaning in an image by looking at it. Computer vision is a method that extracts information from the visual world and helps computers see it. This course will teach you all about Image Analysis techniques, and the importance of computer vision in AI. To increase your understanding of this component, you will learn about the classic Image Analysis techniques like Edge Detection and Watershed, as well K-means Clustering. To understand the history of Image Analysis, you'll be able to learn about the evolution of Image Analysis.

You will be able to use deep learning and classical object classification techniques to apply modern AI technologies by the end of this course. OpenCV and Microsoft Cognitive Toolkit will be used to extract meaningful parts from images. This will allow you to further enhance your computer vision knowledge. OpenCV will teach you how to implement the classic Image Analysis algorithms. You'll also learn how to train a model for Semantic Segmentation using Transfer Learning or Microsoft ResNet. These skills are transferable and will be useful in dealing with computer vision in AI.

Microsoft has granted accreditation to this course