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Microsoft AI-103 Valid Braindumps - Developing AI Apps and Agents on Azure

AI-103
  • Exam Code: AI-103
  • Exam Name: Developing AI Apps and Agents on Azure
  • Updated: Aug 02, 2026
  • Q & A: 159 Questions and Answers
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Microsoft AI-103 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement text analysis and information extraction solutions10-15%- Analyze and extract information
  • 1. Implement natural language processing
  • 2. Extract entities and structured data
  • 3. Use document intelligence services
Topic 2: Implement computer vision solutions10-15%- Analyze visual content
  • 1. Implement OCR and visual understanding
  • 2. Use multimodal vision APIs
  • 3. Process images and video
Topic 3: Implement agentic solutions20-25%- Manage agent operations
  • 1. Monitor and debug agents
  • 2. Secure agent interactions
  • 3. Implement scalable deployments
- Build AI agents
  • 1. Configure memory and orchestration
  • 2. Create autonomous and multi-agent workflows
  • 3. Integrate tools and external knowledge
Topic 4: Implement generative AI solutions25-30%- Optimize and evaluate models
  • 1. Configure content filters and safety
  • 2. Implement multimodal AI capabilities
  • 3. Evaluate responses and grounding
- Develop generative AI applications
  • 1. Implement prompt engineering
  • 2. Build retrieval-augmented generation solutions
  • 3. Use Azure OpenAI and Foundry models
Topic 5: Plan and manage Azure AI solutions25-30%- Plan Azure AI resources
  • 1. Configure authentication and security
  • 2. Select Azure AI services and Foundry resources
  • 3. Manage deployments and monitoring
- Manage AI solution lifecycle
  • 1. Apply responsible AI practices
  • 2. Monitor model and application performance
  • 3. Implement CI/CD for AI applications

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You build a chatbot that uses the Azure OpenAI GPT-4 model to generate song lyrics.
You need to ensure that responses do NOT contain lyrics from popular songs that might have been ingested during model training.
Which Azure AI Content Safety API should you use?

A) Groundedness detection
B) Custom categories
C) Analyze Text
D) Protected material text detection


2. 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.


3. Hotspot Question
You are creating an enrichment pipeline that will use Azure AI Search. The knowledge store contains unstructured JSON data and the text from scanned PDF documents.
Which projection type should you use for each data type? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.


4. You are creating an image-editing workflow in a Microsoft Foundry project.
The workflow must meet the following requirements:
- Ensure that background objects can be removed by applying a mask-
based inpainting edit.
- Preserve the original lighting and style of the edited images.
- Use the built-in image editing controls, NOT a custom model.
You need to ensure that image edits apply exclusively inside the masked area.
How should you configure the workflow?

A) Enable text_to_image mode and a prompt describing the desired background removal.
B) Enable mask_inpainting and supply both the input image and a mask indicating which part of the image to modify.
C) Enable image_to_image mode and a high-strength value to regenerate the full image based on the prompt.
D) Set generation mode to image_variation and provide the original image as a reference.


5. Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
You have a multimodal AI generative model that accepts image uploads and uses extracted image text to generate responses.
You discover that users can upload unsafe images and embed hidden instructions into images to manipulate the model.
You need to implement controls to mitigate the risk.
Solution: You configure a prompt shield for documents.
Does this meet the goal?

A) No
B) Yes


Solutions:

Question # 1
Answer: D
Question # 2
Answer: Only visible for members
Question # 3
Answer: Only visible for members
Question # 4
Answer: B
Question # 5
Answer: B

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