Microsoft Developing AI Apps and Agents on Azure : AI-103 exam

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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

Question 1

You are developing an application that will use Azure AI Search for internal documents.
You need to implement document-level filtering for Azure AI Search.
Which three actions should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Retrieve the group memberships of the user
B. Add allowed groups to each index entry
C. Send access tokens from Microsoft Entra ID, with the search request.
D. Retrieve all the groups.
E. Create one index per group.
F. Supply the groups as a filter for the search requests

Question 2

Hotspot Question
You have a Microsoft Foundry project that contains a deployed chat model.
You have a Python service that sends API requests to the model. The service is integrated with an automated validation system that compares generated outputs against approved response patterns.
Stakeholders report that small wording differences are causing validation mismatches.
You need to update the request parameters to improve output stability. The solution must maximize reasoning quality.
How should you complete the Python code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Question 3

You have a Microsoft Foundry project that contains a customer support agent. The agent calls an internal knowledge API tool before generating responses.
Users report the following issues:
- Some requests take more than 15 seconds to complete.
- Some responses are incorrect, even when the knowledge API returns the expected data.
You need to inspect individual agent runs to view the ordered sequence of large language model (LLM) calls, tool invocations, and timing information.
Which observability capability should you use?

A. token usage
B. tracing
C. safety metrics
D. monitoring

Question 4

You have a Microsoft Foundry agent that grounds responses from an Azure Search index that contains the following:
- Searchable text fields for product names and product codes
- A vector field that stores embeddings for product descriptions
You need to ensure that users can query the index by using the following:
- Exact product names or codes
- Natural language descriptions of the products
What should you configure?

A. keyword search only
B. vector search only
C. semantic search only
D. hybrid search

Question 5

You have a Microsoft Foundry project.
You need to deploy a model from the model catalog to support real-time inference. The solution must meet the following requirements:
- Use key-based authentication.
- Support real-time REST API access.
- NOT consume the vCPU quota of the virtual machines in the Azure
subscription.
Which type of deployment should you use?

A. serverless API
B. self-hosted container
C. batch
D. standard

Solutions: