SkillSoft Explore Course – Lambers, Inc.

IT Skills Cloud Computing and Virtualization Microsoft AI-900: Azure AI Fundamentals

Azure ML provides a suite of services to help with machine learning by providing a single interface to build, manage, deploy, test, and collaborate via the Azure Machine Learning Studio. In this course, you'll learn about the Azure ML services provided, including as Machine Learning designer and automated machine learning. You'll explore how to access and use the Azure Machine Learning Studio and review the Machine Learning features available in the service. In particular, you'll learn about the features of the Computer Vision, Custom Vision, Face, and Form Recognizer services. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.

Asset ID	it_clazaif_02_enus
Course Type	Video Course
Course Category	Cloud Computing and Virtualization

Objectives
AI-900: Azure AI Fundamentals: Machine Learning with Azure Services discover the key concepts covered in this course describe the machine learning services provided by Azure describe the Azure Machine Learning Studio register and signup for an Azure Machine Learning Studio account and access the studio dashboard inspect the Azure ML Studio sidebar components used for creating machine learning workflows describe the features and services provided by the Azure Computer Vision Service describe the uses of the Custom Vision Service describe the features and services provided by the Azure Face service describe the features and capabilities of the Form Recognizer service identify the process and functions of Azure ML Studio for creating, running, and maintaining AI workloads identify and describe the features of a compute target describe a dataset and how they are created and managed manage pipelines in the Azure ML Studio interface describe the limitations and features of automated ML model training describe an experiment and how to run it in Azure ML studio identify and interpret the evaluation metrics for a run of a Classification model identify and interpret the evaluation metrics for a run of a Regression model summarize the key concepts covered in this course

Objectives

AI-900: Azure AI Fundamentals: Machine Learning with Azure Services

discover the key concepts covered in this course
describe the machine learning services provided by Azure
describe the Azure Machine Learning Studio
register and signup for an Azure Machine Learning Studio account and access the studio dashboard
inspect the Azure ML Studio sidebar components used for creating machine learning workflows
describe the features and services provided by the Azure Computer Vision Service
describe the uses of the Custom Vision Service
describe the features and services provided by the Azure Face service
describe the features and capabilities of the Form Recognizer service
identify the process and functions of Azure ML Studio for creating, running, and maintaining AI workloads
identify and describe the features of a compute target
describe a dataset and how they are created and managed
manage pipelines in the Azure ML Studio interface
describe the limitations and features of automated ML model training
describe an experiment and how to run it in Azure ML studio
identify and interpret the evaluation metrics for a run of a Classification model
identify and interpret the evaluation metrics for a run of a Regression model
summarize the key concepts covered in this course