Preparing to Build a Pipeline in Azure Machine Learning Studio

45 minutes
  • 3 Learning Objectives

About this Hands-on Lab

In this lab, you will explore Azure Machine Learning designer. This lab is designed as a complete beginner lab with little to no background in artificial intelligence or machine learning. Azure Machine Learning designer is a great platform to introduce you to machine learning as you can build experiments with little to no code and without a deep understanding of algorithms or high-level math.

Learning Objectives

Successfully complete this lab by achieving the following learning objectives:

Create a Machine Learning Workspace

Create an Azure Machine Learning workspace in the East US 2 region. Once created, become familiar with the interface, including how to access designer as well as create and attach compute to work with a pipeline.

Learn How to Access and Start Built-In Samples

Access the sample library in designer and open instances to provide additional learning opportunities.

  1. Create a STANDARD_DS2_V2 compute instance.
  2. Create a new container registry.
  3. Find and open designer.
  4. Create a new pipeline from the Microsoft sample pipeline: Recommendation – Movie Rating Tweets.
Learn How to Identify the Components of a Machine Learning Experiment in the Sample

Review a sample pipeline and learn to identify core components found in Machine Learning experiments. Conclude by successfully running your first pipeline.

  1. Complete the creation of the new pipeline from the Microsoft sample pipeline: Recommendation – Movie Rating Tweets.
  2. Attach the created compute.
  3. Create a new experiment.
  4. Submit the pipeline.
  5. Find the Recommendations once the pipeline has completed successfully.

Additional Resources


Our company, FlockFuster, Inc., competes with the giants in selling subscription-based television across the world. Eyeing the growth of their competitors and the industry as a whole, they would like to begin adding machine learning to understand how users rate movies.

You have been asked to review and provide insight into what is possible in the space.

In this lab, you will:

1) Learn how to create a Machine Learning designer instance in Azure. 2) Become familiar with the interface. 3) Learn how to access and start built-in samples. 4) Learn how to identify the components of a machine learning experiment in the sample.

Lab Environment Requirements

In this lab, you will be working with Azure Machine Learning. In order to use it, it's necessary to keep the same Azure lab credentials. If the lab times out, make sure to close out Azure Machine Learning and start from scratch.

If you get stuck, feel free to check out the lab objectives or the solution video. Good luck!

WARNING: Be Prepared for UI Changes

Given the fluid nature of Microsoft's cloud tools, students may experience user interface (UI) changes that were made following the development of this hands-on lab that do not match up with the lab instructions. When any such changes are brought to our attention, we will attempt to update the content accordingly. However, if changes occur, students will have to adapt to the changes and work through them in the hands-on labs as needed.

What are Hands-on Labs

Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.

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