Gain machine learning and AI skills

This course is part of the Advanced and Applied AI on Microsoft Azure ExpertTrack, helping you develop AI and machine learning skills and prepare you for the relevant Microsoft microcredentials.

When we look at an image, we are able to pick out meaning based on what we see. When computers are presented with an image, it will usually see nothing unless we use computer vision, a way to extract information and understand the visual world.

During this course, you’ll learn all about Image Analysis techniques and why computer vision is important in AI. You’ll explore classical Image Analysis techniques such as Edge Detection, Watershed and Distance Transformation, as well as K-means clustering to increase your knowledge on this AI component.

Explore the evolution of image analysis

You’ll learn the evolution of Image Analysis to understand the background of this field of AI.

By the end of the course, you’ll be able to compare classical and deep learning object classification techniques and apply them to modern AI technologies.

Segment images using OpenCV and Microsoft Cognitive Toolkit

You’ll gain hands-on experience using OpenCV and the Microsoft Cognitive Toolkit to segment images into meaningful parts and further strengthen your knowledge of computer vision.

In OpenCV, you’ll learn how to implement classic Image Analysis algorithms and you’ll also understand how to train a model to perform Semantic Segmentation using Transfer Learning and Microsoft ResNet. These are transferable skills you will use time and time again when dealing with computer vision in AI.

What topics will you cover?

Current image segmentation techniques
Image features and classical segmentation techniques
Object classification and detection
Deep image segmentation

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Who is this accredited by?

Microsoft:

This course is accredited by Microsoft

Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

Apply classical Image Analysis techniques, such as Edge Detection, Watershed and Distance Transformation as well as K-means Clustering to segment a basic dataset.
Implement classical Image Analysis algorithms using the OpenCV library.
Compare classical and Deep-Learning object classification techniques.
Apply Microsoft ResNet, a deep Convolutional Neural Network (CNN) to object classification using the Microsoft Cognitive Toolkit.

Who is the course for?

This course is for anyone interested in computer vision, with an understanding of the basics of image processing.

Who developed the course?

CloudSwyft Global Systems, Inc.

CloudSwyft has partnered with the top global technology companies to deliver cutting edge digital skills learning across the modern workplace.

About this ExpertTrack

Enhance your understanding of machine learning and AI using Microsoft Azure and Python.

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Only pay while you’re learning; the subscription will cancel automatically when you finish
Complete online assessments to test your knowledge and prove your skills
Earn digital course certificates and a final award that you can share online, with potential employers, and your professional network
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Complete 90% of course steps and all of the assessments to earn your certificate

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