Microsoft AI-901 : Microsoft Azure AI Fundamentals

  • Exam Code: AI-901
  • Exam Name: Microsoft Azure AI Fundamentals
  • Updated: Oct 14, 2026
  • Q & A: 132 Questions and Answers

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Microsoft AI-901 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Identify AI concepts and capabilities: This domain covers the foundational knowledge of AI from ethical principles and responsible design to understanding how AI models work and what kinds of tasks they can perform. It also explores the full range of AI workloads including generative AI, computer vision, speech, and information extraction.
Topic 2
  • Implement AI solutions by using Microsoft Foundry: This domain is hands-on and focuses on building and deploying AI solutions using the Microsoft Foundry platform and its associated tools. It spans generative AI apps, text and speech processing, computer vision, and document intelligence all implemented through the Foundry portal and SDK.

Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-901

Microsoft Azure AI Fundamentals Sample Questions:

Question #1

You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You use the Azure OpenAI Responses API to send a prompt to the model.
You need to provide an image for analysis.
Which content item should you include in the request?

  • A. image_generation
  • B. input_image
  • C. image_base64
  • D. output_image
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #2

For each of the following statements, select Yes if the statement is true. Otherwise, select NOTE Each correct selection is worth one point.

Reveal Solution  Discussion  0

Correct Answer:


Explanation:

Statement 1: Azure Content Understanding in Foundry Tools can analyze only PDF documents. = No Azure Content Understanding is not limited to PDF documents. It can analyze multiple content types, including documents, forms, images, audio, and video.
Statement 2: Azure Content Understanding in Foundry Tools results are returned in the JSON format. = Yes Azure Content Understanding returns structured analysis results in JSON format. This is how extracted fields, values, confidence scores, and other analysis results are represented.
Statement 3: Azure Content Understanding in Foundry Tools can extract structured fields from documents and forms. = Yes Azure Content Understanding can use analyzers and schemas to extract structured fields from documents and forms, such as invoices, receipts, contracts, and other business documents.

Question #3

You are developing an application that uses the Azure Language SDK and a Microsoft Foundry resource.
You need to return a list of important topics from unstructured text.
Which Python method should you use?

  • A. client.begin_extract_summary()
  • B. client.extract_key_phrases()
  • C. client.recognize_linked_entities()
  • D. client.recognize_entities()
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #4

You have a Microsoft Foundry project that contains a vision-enabled GPT model deployment You need to develop an application that sends an image and a text question to the model in a single request.
What should you use?

  • A. the Azure OpenAI Responses API
  • B. the Speech to text REST API
  • C. the Alure OpenAI Images API endpoint only
  • D. the Image Analysis REST API
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #5

Select the answer that correct completes the sentence.

Reveal Solution  Discussion  0

Correct Answer:


Explanation:
Azure Text Analytics client library
The completed sentence is:
To develop an application that analyzes text by using Azure Language in Foundry Tools, use the Azure Text Analytics client library package.
Azure Language text analysis features include sentiment analysis, key phrase extraction, named entity recognition, language detection, and other text analytics capabilities. These are accessed by using the Azure Text Analytics client library.
The highlighted Azure Speech SDK option is incorrect because it is used for speech workloads, such as speech recognition and speech synthesis, not text analysis.

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