Microsoft Azure AI Fundamentals (Updated Version) AI-901 Exam Questions

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Total 50 questions
Question 1

You need to build an AI solution that generates marketing email drafts based on a short description of a product and its target audience.

Which AI workload should you use?



Answer : A

Generating marketing email drafts from a short product description and target audience is a content generation task. This is a generative AI workload because the system creates new text based on the user's prompt.

B . computer vision is for interpreting images or video. C . text classification categorizes existing text, but does not draft new marketing emails. D . speech recognition converts spoken audio into text.

Therefore, the correct answer is A. generative AI.


Question 2

Your company processes customer support emails.

You need to implement an AI solution that automatically identifies mentions of people, organizations, and locations in the emails.

Which text analysis technique should you use?



Answer : B

The correct text analysis technique is Named Entity Recognition (NER).

Microsoft defines NER as a feature that identifies and categorizes entities in unstructured text, including people, places, and organizations.

Sentiment analysis detects positive, negative, or neutral opinion. Summarization creates shorter versions of text. Key phrase extraction identifies important phrases, but it does not specifically classify mentions as people, organizations, or locations.


Question 3

Based on the image provided, here is the transcribed text:

You need to build an AI solution that produces new product images based on written descriptions provided by users.

Which AI workload should you use?



Answer : A

The requirement is to produce new product images based on written descriptions. This is an image generation workload, because the AI system is creating entirely new images from natural language prompts.

Why the other options are incorrect:

B . image analysis is used to examine and interpret existing images.

C . object detection is used to identify and locate objects within an existing image.

D . optical character recognition (OCR) is used to extract text from images or scanned documents.

Since the solution must generate new visual content from user-provided descriptions, the correct answer is:

A . image generation


Question 4

You have a Microsoft Foundry project that has a generative AI model deployment.

You need to ensure that responses generated by the model minimize costs and remain within a defined length.

Which parameter should you configure?



Answer : B

To minimize cost and keep generated responses within a defined length, configure Max Completion Tokens.

Microsoft's Azure OpenAI / Foundry API reference defines max_completion_tokens as an upper bound for the number of tokens that can be generated for a completion. Because generated tokens contribute to usage and response length, limiting completion tokens helps control both output length and cost.

Temperature and Top P control randomness or sampling behavior, not maximum response length. Model version settings do not directly define the generated response length.


Question 5

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

You are developing an application that sends images to the model.

You need to ensure that the model can analyze the images.

In which two formats can you provide the images? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.



Answer : C, D

For vision-enabled Azure OpenAI / Microsoft Foundry model requests, image input can be provided by using an image URL or base64-encoded image data. Microsoft's Azure OpenAI REST API reference states that the image content part URL field can contain either a URL of the image or the base64 encoded image data. It also states that the Responses API input_image.image_url value can be a fully qualified URL or a base64 encoded image in a data URL.


Question 6

You need to compare the costs of large language models (LLMs) for a generative AI solution.

What should you use in the Microsoft Foundry portal?



Answer : B

To compare the costs of large language models in Microsoft Foundry portal, use the Model leaderboard.

Microsoft documentation states that the model leaderboard helps compare models across quality, safety, estimated cost, and throughput. It also supports trade-off charts and side-by-side model comparison for features, performance, and estimated cost.

Why the other options are incorrect:

A . Evaluator catalog is for selecting evaluators to measure model or application outputs, not comparing LLM costs. C . Compliance relates to governance and compliance, not model cost comparison. D . Tools provides Foundry tools, not benchmarked cost comparison across models.


Question 7

What are two purposes of instructions when prompting a generative AI model? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.



Answer : A, B

Microsoft Foundry Agent Service documentation states that instructions define goals, constraints, and behavior for an agent. Therefore, instructions are used to guide how the generative AI model or agent should respond and behave.

Option A is correct because instructions can define constraints the model must follow.

Option B is correct because instructions can define the agent's role and behavior.

Options C, D, and E are incorrect because Azure region, model selection, and TPM allocation are configuration or deployment/resource settings, not purposes of prompt instructions.


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Total 50 questions