Create and manage resources in a Machine Learning workspace
11 practice questions under this official exam objective (AI-300), each with the answer key, an option-by-option explanation and instant feedback.
Questions under this objective
11 total · page 1 of 1Azure ML Compute Targets for Experimentation vs Training
This page explains how to map Azure Machine Learning workloads to appropriate compute targets. Interactive experimentation requires a Compute Instance
Updating Azure ML Environments with New Docker Images
Learn how to update an Azure Machine Learning environment to use a new Docker image by creating a new version using the SDK v2 Environment class, as e
Azure ML Workspace Managed Identity Git Access
Learn how to configure Azure Machine Learning workspace managed identity for secure, centralized Git repository access without local tokens.
Creating a New Jupyter Kernel in Azure ML Compute Instance
This page explains how to add a new Jupyter kernel to an Azure ML compute instance by creating a Conda environment, activating it, installing requirem
Ensuring Consistent Runtime Dependencies with Azure ML Environments
Learn how to resolve inconsistent runtime dependencies in Azure Machine Learning by correctly implementing an Azure ML Environment for reproducible mo
Cloning GitHub Repositories to Azure ML Workspaces via SSH
Learn the correct sequence to clone a GitHub repository into an Azure Machine Learning shared workspace using SSH key authentication and git commands.
Maximizing Git Clone Performance in Azure ML Workspace
To maximize performance when cloning a private GitHub repo to Azure ML WS1, create a compute instance, open a terminal, generate an SSH key pair, and
Configuring Time-Limited Azure Blob Datastore Access in SDK v2
Learn how to configure an Azure Blob datastore in Azure ML SDK v2 using the correct container name and time-limited SAS token credentials.
Azure ML Hub and Projects Governance Model
Learn how to establish governed MLOps in Azure by implementing the Hub and Projects workspace architecture for multi-team isolation and central contro
Azure ML Python SDK v2 FAILED Status Interpretation
This question tests the interpretation of Azure Machine Learning experiment run statuses using the Python SDK v2, specifically distinguishing between
Azure ML Python SDK v2: Importing Labeled Image Data for Automated ML
This scenario tests the correct Azure Machine Learning Python SDK v2 syntax for importing labeled image data as an input asset. The solution requires