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Microsoft AI-103 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement text and speech analysis solutions | 10–15% | - Implement natural language processing
|
| Topic 2: Plan and manage Azure AI solutions | 25–30% | - Manage AI solution development lifecycle
|
| Topic 3: Implement computer vision solutions | 10–15% | - Build multimodal solutions
|
| Topic 4: Implement information extraction and knowledge mining | 10–15% | - Extract structured data from documents
|
| Topic 5: Implement generative AI and agentic solutions | 30–35% | - Build generative AI applications
|
Microsoft Developing AI Apps and Agents on Azure Sample Questions:
1. Hotspot Question
You plan to create a Microsoft Foundry project named Project1 that will contain an agent and use an Azure key vault named KV1.
You need to configure a connection from Project1 to KV1.
How should you complete the Bicep code? To answer, select the appropriate options in the answer area?
NOTE: Each correct selection is worth one point.
2. You have an Azure subscription that contains an Azure Al Foundry instance named AI1.
You have an app that automatically triages and resolves issues presented in the log files of a system.
You create an incident manager agent and a DevOps agent that collaborate to resolve the issues.
You need to ensure that the incident manager agent can assign work to the DevOps agent. The solution must minimize development effort.
What should you do?
A) Create a plugin for the DevOps agent.
B) Configure prompt flow for AI1.
C) Create a plugin for the incident manager agent.
D) Configure a connected agent for AI1.
3. 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.
4. You have an app named App1 that uses a Microsoft Foundry multimodal model deployment.
App1 runs optical character recognition (OCR) on uploaded images and appends the OCR output to the prompt as additional context.
Some uploaded images contain embedded text.
You need to prevent potentially malicious instructions from being processed by the model.
What should you use?
A) prompt shields for documents
B) image moderation
C) protected material text
D) prompt shields for user prompts
5. You need to add an automated grounding check to a RAG application's continuous evaluation.
The check must return a simple pass or fail result and must not require you to deploy a separate judge model. Which evaluator should you use?
A) Groundedness, which returns a 1 to 5 score
B) Fluency
C) Groundedness Pro
D) Relevance
Solutions:
| Question # 1 Answer: Only visible for members | Question # 2 Answer: D | Question # 3 Answer: Only visible for members | Question # 4 Answer: A | Question # 5 Answer: C |





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