SkillSoft Explore Course – Lambers, Inc.

Certification Microsoft Microsoft Certified: Azure AI Fundamentals AI-900: Azure AI Fundamentals

Computer vision is the machine learning capability to allow computers to "see" similar to how a person can see, and be able to identify, distinguish, and interpret objects, people, and even text from images or video. In this course you will learn about the Azure ML Computer Vision service, Computer Vision Models, and how it can be trained and used to detect and classify objects in images and videos using a Classifier model and semantic segmentation. Youâll also learn how to evaluate the results of an object detection model. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.

Asset ID	it_clazaif_09_enus
Course Type	Video Course
Course Category	Microsoft

Objectives
AI-900: Azure AI Fundamentals: Computer Vision discover the key concepts covered in this course describe how computer vision works and how it can be used to solve real world problems recognize the features and capabilities of the Azure Computer Vision services identify the different Computer Vision models available for doing image classification, object detection, and image analysis describe how Computer Vision identifies real world items and objects use the Computer Vision service to analyze images use studio to describe and tag images used for training a classification model training a classifier to classify items in an image evaluate the results of the classifier model deploy and test the prediction capabilities of the Model train a model to detect objects in an image evaluate the results of an object detection model deploy and test the model as a service describe the purpose and uses of semantic segmentation summarize the key concepts covered in this course

Objectives

AI-900: Azure AI Fundamentals: Computer Vision

discover the key concepts covered in this course
describe how computer vision works and how it can be used to solve real world problems
recognize the features and capabilities of the Azure Computer Vision services
identify the different Computer Vision models available for doing image classification, object detection, and image analysis
describe how Computer Vision identifies real world items and objects
use the Computer Vision service to analyze images
use studio to describe and tag images used for training a classification model
training a classifier to classify items in an image
evaluate the results of the classifier model
deploy and test the prediction capabilities of the Model
train a model to detect objects in an image
evaluate the results of an object detection model
deploy and test the model as a service
describe the purpose and uses of semantic segmentation
summarize the key concepts covered in this course