About the Exam

This exam is for candidates at the beginning of their career in AI solution development. It measures conceptual knowledge of AI solutions in Azure, foundational technical skills, Python coding basics, and familiarity with Azure resources. Passing demonstrates you can describe AI workloads and considerations, machine learning fundamentals on Azure, computer vision, NLP, and generative AI workloads, and implement AI solutions by using Microsoft Foundry.

Exam Topics

  • Identify AI concepts and capabilities40–45%
  • Implement AI solutions by using Microsoft Foundry55–60%

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Last updated July 10, 2026 at 1:31 AM

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QuestionQ1

Implement AI solutions by using Microsoft Foundry

You need to transform written customer notifications into natural-sounding spoken audio for playback through a phone system.

Which Azure Speech in Foundry Tools capability should you use?

  • A speech recognition
  • B speech synthesis
  • C speaker recognition
  • D speech translation
Explanation

Speech synthesis, also called text to speech, converts written text into human-like synthesized spoken audio, including for application and phone-system playback.

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QuestionQ2

Implement AI solutions by using Microsoft Foundry

You have a Microsoft Foundry project containing a vision-enabled model deployment.

You use the Azure OpenAI Responses API to send a prompt to the model. You need to supply an image for analysis.

Which content item should be included in the request?

  • A image_generation
  • B output_image
  • C input_image
  • D image_base64
Explanation

For a vision-enabled model, the Azure OpenAI Responses API uses an input_image content item to provide an image for analysis. Its image_url field can contain either an image URL or a Base64-encoded image as a data URL.

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QuestionQ3

Identify AI concepts and capabilities

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

Yes or No
StatementsYesNo
System prompts can be used to authorize users.
A system prompt is used to reduce tokens per minute (TPM).
A system prompt guides the behavior of a generative AI model.
Explanation

System prompts provide instructions and context that steer model behavior, such as role, tone, boundaries, and output format. They do not authenticate or authorize users, which must be enforced by the application’s identity and access-control mechanisms. A system prompt consumes context/input tokens rather than reducing a tokens-per-minute limit.

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QuestionQ4

Implement AI solutions by using Microsoft Foundry

You are building an application that analyzes voicemail recordings by using Azure Content Understanding in Foundry Tools.

You need to extract a transcript and structured data from the recordings.

Which analyzer type should you use?

  • A document analyzer
  • B video analyzer
  • C audio analyzer
  • D image analyzer
Explanation

Audio analyzers in Azure Content Understanding transcribe conversational audio and extract structured fields from audio files, making them suitable for voicemail recordings.

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QuestionQ5

Identify AI concepts and capabilities

Select the answer that correctly finishes the sentence.

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Topics covered
Identify AI concepts and capabilitiesImplement AI solutions by using Microsoft Foundry
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