AI-300 Practice Test

AI-300 Practice Test practice questions, page 5 of 7, with answer review and explanations.

Question 21

You have an existing GitHub repository containing Azure Machine Learning project files. You need to clone the repository to your Azure Machine Learning shared workspace file system. Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Question 22

You manage an Azure Machine Learning workspace. You have an environment for training jobs which uses an existing Docker image. A new version of the Docker image is available. You need to use the latest version of the Docker image for the environment configuration by using the Azure Machine Learning SDK v2. What should you do?

  1. Change the description parameter of the environment configuration.
  2. Modify the conda_file to specify the new version of the Docker image.
  3. Use the create_or_update method to change the tag of the image.
  4. Use the Environment class to create a new version of the environment.

Question 23

You manage an Azure Machine Learning workspace. You need to define an environment from a Docker image by using the Azure Machine Learning Python SDK v2. Which parameter should you use?

  1. conda_file
  2. properties
  3. build
  4. image

Question 24

A company has multiple data science teams working on separate machine learning projects. The company requires models to be auditable, reusable, and governed centrally across teams. The models must allow team-level isolation for billing. You need to establish the foundation for governed machine learning operations. Which action should you perform first?

  1. Register shared datasets in a central storage account.
  2. Create a shared hub workspace and project workspaces for each team.
  3. Create a resource group for shared machine learning assets.
  4. Create a shared Azure Machine Learning workspace.

Question 25

A team provisions an Azure Machine Learning environment by triggering pull requests. Deployments must be automated, auditable, and require approval before running. You need to select a deployment automation tool. Which tool should you use?

  1. Azure Monitor
  2. GitHub Actions
  3. MLflow
  4. Azure Machine Learning pipelines