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

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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

Question 1

Hotspot Question
You have a Microsoft Foundry project that contains two agents named PolicyWriter and RskReviewer.
PolicyWriter generates daft updates for customer polices, and RiskReviewer reviews the drafts.
In the visual builder, you need to create a workflow that meets the following requirements:
- Finalizes low-risk updates without manual intervention
- Ensures predictable execution across the agents
- Requires user approval for highs updates
What should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each comet selection is worth one point.

Question 2

Hotspot Question
You have an Azure subscription.
You need to create a new resource that will generate fictional stores in response to user prompts.
The solution must ensure that the resource uses a customer-managed key to protect data.
How should you complete the script? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Question 3

You plan to build an agent that will combine and process multiple files uploaded by users.
You are evaluating whether to use the Azure AI Agent Service to develop the agent.
What is the maximum size of each file that can be uploaded to the service?

A. 256 MB
B. 1 GB
C. 10 MB
D. 512 MB

Question 4

You have a Microsoft Foundry project that contains a Retrieval Augmented Generation (RAG) chat solution used by customer support agents.
You are adding an automated pre-production evaluation step to a CI/CD pipeline named Pipeline1. The evaluation will run against a labeled test dataset that contains support questions and the expected grounding context.
You need to ensure that Pipeline1 fails if unsupported content or a retrieval mismatch exceeds a defined threshold:
- responses include claims not supported by the retrieved source
content
- retrieved source content does not align with the labeled expected
context
Which two built-in evaluators should you use in Pipeline1? Each correct answer presents pat of the solution.
NOTE: Each correct selection is worth one point.

A. Fluency
B. Groundedness
C. Response Completeness
D. Coherence
E. Retrieval

Question 5

You have a product support manual.
You need to build a product support chatbot based on the manual. The solution must minimize development effort and costs.
What should you use?

A. Azure AI Language Custom question answering
B. Azure AI Document intelligence
C. Azure OpenAI GPT-4 with grounding data that uses Azure AI Search
D. Azure AI Phi-3-medium with fine-tuning

Solutions: