hands-on lab

Introduction to Azure Machine Learning Studio

2h 15m
Get guided in a real environmentPractice with a step-by-step scenario in a real, provisioned environment.
Learn and validateUse validations to check your solutions every step of the way.
See resultsTrack your knowledge and monitor your progress.
Lab description

The Azure Machine Learning Studio enables Data Scientists and Developers of different skillsets to harness the power of Azure to manage their Machine Learning experiments. Scalable compute resources can be used to process data science tasks without any up-front hardware investment. Pipelines allow ML engineers to bring CI/CD's operational efficiency to their day-to-day tasks. The Azure ML Studio gives a no-code experience through the Designer tool and only-code interaction through Azure Notebooks.

In this lab, you will explore Azure Machine Learning Studio and use the Designer tool to create a Machine Learning Pipeline and deploy it as a web service. This lab involves running two pipelines that can each take up to 15 minutes to complete. Please make sure you have enough time available before starting this lab.

Learning Objectives

Upon completion of this lab you will be able to:

  • Manage a machine learning experiment
  • Use the Azure ML Designer tool
  • Deploy an Azure ML Pipeline as a web service
  • Build Azure ML Pipelines for your Data Science workflows

Intended Audience

This lab is intended for:

  • Individuals studying to take the Azure DP-100 exam
  • Anyone interested in learning how to use the Azure Machine Learning Studio

Lab Prerequisites

You should be familiar with:

  • Basic concepts of Azure Machine Learning


January 26th, 2024 - Updated the instructions and screenshots to reflect the latest UI

April 6th, 2023 - Updated the instructions and screenshots to reflect the latest UI

October 17th, 2022 - Updated screenshots & instructions due to UI updates

December 16th, 2021 - Provided a workaround for when the real-time inference endpoint deployment times out

November 8, 2021 - Upgraded compute unit in ML studio

September 30, 2021 - Updated lab instructions to fix the access issue with the Machine learning studio

Environment before
Environment after
About the author
Learning paths

Luke is a Site Reliability Engineer at Microsoft. His background is infrastructure development using Terraform and in 2021 he was awarded the HashiCorp Ambassador award. He is an Azure DevOps Engineer Expert, Azure Administrator Associate, and HashiCorp Certified - Terraform Associate.

Covered topics
Lab steps
Logging in to the Microsoft Azure Portal
Exploring the Azure Machine Learning Studio
Designing a Machine Learning Pipeline
Running the Azure Machine Learning Pipeline
Create a Real-Time Inference Pipeline and Deploy an Endpoint