Cloud-based platform Microsoft Azure has multiple AI services which could be used to train your model for big data sets as well as to deploy your model as a web service. In this course, Optimizing Microsoft Azure AI Solutions, you will learn the foundational knowledge of how to train your machine learning models using Azure’s services such AzureML Compute Cluster, Azure HDInsight, Azure Databricks, and Azure Data Science Virtual Machine. Next, you will discover how to optimize your storage by using Azure Premium blob storage service and data formats such as Pickle and Parquet. Finally, you will explore how to scale your machine learning models and manage end-to-end machine learning life cycle using the principle of MLOps. When you’re finished with this course, you will have the skills and knowledge of Mircosoft Azure’s core AI services needed to design, deploy, and optimize your model.
Author Name: Ranjan Relan
Author Description:
Ranjan Relan is a Founder/CTO of GenAI company – AgentAnalytics.com . He previously worked as AI, Data and Tech Strategy Consultant with more than 16+ years of experience in the field of Analytics which includes working on Machine Learning, Big data and Data ware housing projects. He has helped clients across Hi Tech, Telecom and Pharma domain in developing data strategy, cloud adoption strategy, analytics strategy ,solution architecture.

Table of Contents

• Course Overview
  1min
• Optimizing Core Services
  33mins
• Optimizing Storage and Logging
  18mins
• Optimizing Deployments and Operations
  33mins