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

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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. Hotspot Question
Your company is piloting a customer support agent in a Microsoft Foundry project name Project1.
Project1 is connected to an existing Application Insights resource, and the company's support team reviews runs in the Traces tab.
The Foundry Agent Service is configured to perform the following actions:
- Retrieve the Application Insights connection string by calling
project_client.telemetry.get_application_insights_connection_string().
- Call configure_azure_monitor(connection_string=...) to enable
telemetry.
A separate LangChain service is configured to use OpenTelemetry and has the following configurations:
- Uses AzureAIOpenTelemetryTracer(connection_string=...,
enable_content_recording=False)
- Passes the tracer by using config={"callbacks":[azure_tracer]}
Company policy has the following requirements:
- Telemetry from LangChain and OpenTelemetry must be distinguishable
within the same Application Insights resource.
- Secrets and credentials must NOT be stored in prompts, tool
arguments, or span attributes.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

2. You have a custom agent named Agent1.
You need to control access to and monitor activity for Agent1 by using Microsoft Foundry.
What should you do first?

A) Provision an Application Insights resource.
B) Add Agent1 to the Microsoft Foundry playground.
C) Create a Microsoft Foundry project.
D) Add Agent1to a Microsoft Foundry project.

3. A legal team must extract clauses and inferred fields from unstructured contracts. One required field is the contract end date, which is not stated explicitly and must be derived from the start date plus the term. The team has no labelled training data. Which tool best fits?

A) Azure Translator in Foundry Tools
B) The Azure AI Search semantic ranker
C) Azure Content Understanding using a prebuilt-contract or zero-shot custom analyser
D) An Azure AI Document Intelligence custom model trained on labelled samples

4. Hotspot Question
You are building a model to detect objects in images.
The performance of the model based on training data is shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

5. Hotspot Question
You have a Microsoft Foundry project that contains a customer support application.
You create an evaluation named Run1 that has the following configurations:
- Includes risk and safety metrics
- Includes the protected material evaluation
- Includes harmful content metrics that use a medium severity threshold You create an evaluation named Run2 that has the following configurations:
- Includes risk and safety metrics
- Includes the protected material evaluation
- Includes harmful content metrics that use a high severity threshold
You run both evaluations against a dataset named DB1 and receive the following results:
- Content harm defect rate of Run1: 12%
- Content harm defect rate of Run2: 4%
- Protected material evaluation of Run1: 6%
- Protected material evaluation of Run1: 6%
You start a fine-tuning job by using DB1. The job fails during automatic RAI checks for multiple content harm types.
You discover that the content filtering configuration is set to high severity.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Solutions: