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Microsoft

AI-102 · Question #316

Drag and Drop Question You plan to implement an Azure AI Search resource that will use custom skill based on sentiment analysis. You need to create a custom model and configure Azure AI Search use…

The correct answer is Create an Azure Machine Learning workspace.; Provision an Azure AI Services resource and obtain the endpoint.; Create and train the model in the Azure Machine Learning studio.; Create an endpoint for the model.; Connect the custom skill to the endpoint. The correct sequence follows the logical workflow for implementing a custom ML-based skill in Azure AI Search: first establish the Azure Machine Learning workspace as the foundation, then provision Azure AI Services for supporting capabilities, train the custom sentiment model…

Submitted by jian89· Mar 30, 2026Implement knowledge mining and document intelligence solutions – specifically designing and implementing a custom skill pipeline using Azure Machine Learning within Azure AI Search indexers and skillsets.

Question

Drag and Drop Question You plan to implement an Azure AI Search resource that will use custom skill based on sentiment analysis. You need to create a custom model and configure Azure AI Search use the model. Which five 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. Answer:

Exhibit

AI-102 question #316 exhibit

Answer Area

Drag items

Create an endpoint for the model.Rerun the indexer to enrich the index.Create an Azure Machine Learning workspace.Create and train the model in the Azure Machine Learning studio.Provision an Azure AI Services resource and obtain the endpoint.Connect the custom skill to the endpoint.

Correct arrangement

  • Create an Azure Machine Learning workspace.
  • Provision an Azure AI Services resource and obtain the endpoint.
  • Create and train the model in the Azure Machine Learning studio.
  • Create an endpoint for the model.
  • Connect the custom skill to the endpoint.

Explanation

The correct sequence follows the logical workflow for implementing a custom ML-based skill in Azure AI Search: first establish the Azure Machine Learning workspace as the foundation, then provision Azure AI Services for supporting capabilities, train the custom sentiment model in AML Studio, expose it via an endpoint, connect that endpoint as a custom skill in the Azure AI Search skillset, and finally rerun the indexer to apply the enrichment pipeline to the index. This order ensures each dependency is in place before the next step can be configured. Skipping or reordering these steps would result in missing infrastructure or unresolvable references during configuration.

Topics

#Azure AI Search#Custom Skills#Azure Machine Learning#Cognitive Search Enrichment

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