Microsoft : AI-103 Questions & Answers
Updated: Aug 02, 2026
No. of Questions: 159 Questions & Answers with Testing Engine
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Microsoft AI-103 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement information extraction and knowledge mining | 10–15% | - Extract structured data from documents
|
| Topic 2: Implement generative AI and agentic solutions | 30–35% | - Build generative AI applications
|
| Topic 3: Plan and manage Azure AI solutions | 25–30% | - Design Azure AI infrastructure
|
| Topic 4: Implement computer vision solutions | 10–15% | - Implement image analysis and processing
|
| Topic 5: Implement text and speech analysis solutions | 10–15% | - Implement speech capabilities
|
Microsoft Developing AI Apps and Agents on Azure Sample Questions:
1. You have a Microsoft Foundry project that generates product marketing images from text prompts.
After publishing several images, the legal team at your company identifies a competitor's logo on a sign in the background of an image.
You need to remove only the logo, while preserving the rest of the image.
What should you do?
A) Apply a mask-based inpainting edit to the part of the image that contains the logo.
B) Increase the prompt guidance strength.
C) Modify the original prompt to exclude brand names.
D) Rerun the prompt by using a different random seed.
2. You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
You need to improve response completeness. The solution must be implemented in the logic of the application code before responses are returned.
What should you do?
A) Increase the value of the presence_penalty parameter
B) Decrease the value of the temperature parameter.
C) Add a retry evaluation before the responses are returned.
D) Replace the model with a smaller deployment.
3. You have a web app named App1 that processes user prompts by integrating with a Microsoft Foundry project named Project1. App1 performs the following actions:
- Sends prompts directly to a model by using the Azure OpenAI Responses API
- Invokes the Azure AI Content Safety tool by using a Foundry
connection within the same request
You need to configure end-to-end visibility into each step of the request workflow.
What should you do?
A) Enable logging by using the client SDK for Content Safety.
B) Enable logging by using Foundry Local.
C) Route requests through the Azure OpenAI endpoint.
D) Enable application tracing in Project1.
4. You are building an Azure AI Search indexing pipeline named Pipeline1 that ingests invoices stored in Azure Blob Storage. The invoices are stored as scanned images.
You need to enable users to search invoice data across the invoice fields.
Which built-in skill should you add to the skillset of Pipeline1?
A) Text Split
B) Image Analysis
C) Text Translation
D) optical character recognition (OCR)
5. Drag and Drop Question
You have a Microsoft Foundry project that processes procurement documents submitted by suppliers.
You need to implement two pipelines by using Azure Content Understanding in Foundry Tools.
The solution must meet the following requirements:
- Include a pipeline named Pipeline1 that supports cost-effective,
high-volume processing of standalone PDF invoices.
- Include a pipeline named Pipeline2 that supports cross-document
validation by using multi-step reasoning and reference data.
How should you configure each pipeline? To answer, drag the appropriate configurations to the correct pipelines. Each configuration may be used once, more than once, of not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: Only visible for members |
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