Exam DP-100 topic 2 question 52 discussion

On exam 2021/7/10 My answers: ABC Correct options: A . Run Python code that uses the Azure ML SDK library and calls the Workspace.create method with name, subscription_id, resource_group, and location parameters. B . Use an Azure Resource Management template that includes a Microsoft.MachineLearningServices/ workspaces resource and its dependencies. C . Use the Azure Command Line Interface (CLI) with the Azure Machine Learning extension to call the az group create function with –name and –location parameters, and then the az ml workspace create function, specifying Cw and Cg parameters for the workspace name and resource group. D . Navigate to Azure Machine Learning studio and create a workspace. E . Run Python code that uses the Azure ML SDK library and calls the Workspace.get method with name, subscription_id, and resource_group parameters.

I'm confused - Why is B and D the same answer option?

Option A uses the SDK to programmatically create the workspace Option B leverages the visual interface to create the workspace Option C uses CLI commands to automatically create both resource group and workspace

Answers should be ABD : https://learn.microsoft.com/en-us/azure/machine-learning/concept-workspace?view=azureml-api-2 Workspace management task | Portal | Studio | Python SDK |Azure CLI | VS Code Create a workspace | ✓ | ✓ | ✓ | ✓ | ✓

BCD. az group create --name <resource-group-name> --location <location> ws_basic = ml_client.workspaces.begin_create(ws_basic).result() print(ws_basic)

C is a definite option, and B also seems right

On Exam 17 Feb 2023

A. Run Python code that uses the Azure ML SDK library and calls the Workspace.create method with name, subscription_id, and resource_group parameters. B. Navigate to Azure Machine Learning studio and create a workspace. C. Use the Azure Command Line Interface (CLI) with the Azure Machine Learning extension to call the az group create function with --name and --location parameters, and then the az ml workspace create function, specifying "w" and "g" parameters for the workspace name and resource group. Option D. Navigate to Azure Machine Learning studio and create a workspace. is a correct answer, but it is a duplicate of option B. So, the correct answers are A, B, and C

I think, but not 100% sure that the code for creation of a workspcace is workspaces.begin_create and not Workspaces.create as described in option A. example: ml_client.workspaces.begin_create(ws) https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-workspace?tabs=python

A cannot consider before creating a workspace, yes we can create through different methods of CICD but it's not considered here

If D is create workspace by Azure Machine Learning Studio, it is true! https://ml.azure.com/ You can go to https://ml.azure.com/ to create a new workspace.

Why not ACD?

A is wrong: Cannot create a workspace this way because resource group does not yet exist.

With the correct options, ABC no doubt!

Option D is a repeat

Use Azure portal Python SDK or Azure CLI Use Resource Manager template https://docs.microsoft.com/en-us/azure/machine-learning/how-to-manage-workspace?tabs=python

Use Azure portal or Python SDK Use Azure CLI Use Resource Manager template This is from the https://docs.microsoft.com/en-us/azure/machine-learning/how-to-manage-workspace?tabs=python