- Course
- Cloud
Azure ML Workspace Fundamentals
Learn how to provision and manage Azure Machine Learning infrastructure. This course will teach you to configure workspaces, compute targets, environments, and datasets to support scalable ML operations in the cloud.
What you'll learn
As organizations scale their machine learning initiatives, the need for a robust and well-configured ML platform becomes critical. In this course, Azure ML Workspace Fundamentals, you’ll learn to support, deploy, and troubleshoot infrastructure for Azure Machine Learning. First, you’ll explore how to create and connect to Azure ML workspaces and understand how they integrate with ARM resources like storage and key vaults. Next, you’ll discover how to provision compute targets and register datasets for experimentation. Finally, you’ll learn how to create reusable environments and apply governance best practices. When you’re finished with this course, you’ll have the skills and knowledge of Azure ML infrastructure management needed to support real-world enterprise ML workflows at scale.
Table of contents
About the author
Deepak Goyal is a technology expert and instructor with deep experience in cloud, data engineering, AI, architects, and leadership.