Machine learning and the Azure Artificial Intelligence (AI) platform allow you to use existing data to forecast future behaviors, outcomes, and trends. In this course, Operationalizing Microsoft Azure AI Solutions, you’ll focus on what it means to operationalize AI in Microsoft Azure. First, you’ll go through the lifecycle of an AI model, creating the model in Azure Databricks and Azure Machine Learning Services. Next, you’ll discover how to deploy the model into Azure’s version control tool, Azure Devops, and containerize it such that it can be used by the end user. Finally, you’ll explore how to identify integration points with other Microsoft services and the containers used in Azure – Azure Container Instances and Azure Kubernetes Services. When you’re finished with this course, you’ll have the skills and knowledge of Microsoft Azure needed to devise a strategy for managing version control of an AI solution.
Author Name: Dayo Bamikole
Author Description:
Dayo is a Technology Specialist with expertise in Cloud Data Solutions, Artificial intelligence, and Web Development. Dayo has traveled around the United States delivering workshops on technical services in the workplace, in over 35 states, as well as Europe. The audience for these workshops varies from Database Administrators to Software Developers. Ifedayo holds several certifications in Azure, such as: Azure Data Engineer, Azure Data Scientist, Azure AI Engineer, Google Cloud Fundamentals and… more

Table of Contents

• Course Overview
  1min
• Assembling Appropriate Tools and Technologies
  18mins
• Designing a Version Control Strategy for a Microsoft Azure AI Solution
  24mins