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Microsoft AI-901 Exam Syllabus Topics:

SectionWeightObjectives
Implement AI solutions by using Microsoft Foundry55-60%- Get started with Microsoft Foundry
  • 1. Create and configure a Foundry project
  • 2. Navigate the Microsoft Foundry portal
  • 3. Describe core features and use cases of Microsoft Foundry
- Implement AI solutions
  • 1. Monitor and manage AI solutions
  • 2. Use code examples to call AI services
  • 3. Implement single-agent solutions
  • 4. Integrate AI services into applications
- Work with models in Microsoft Foundry
  • 1. Customize models with prompt engineering
  • 2. Discover and deploy foundation models
  • 3. Fine-tune models
  • 4. Evaluate model performance and safety
Identify AI concepts and responsibilities40-45%- Identify AI concepts and features
  • 1. Describe capabilities of machine learning
  • 2. Describe types of AI workloads
  • 3. Describe characteristics of generative AI
  • 4. Describe capabilities of computer vision
  • 5. Describe capabilities of natural language processing
- Identify AI model components and configurations
  • 1. Describe model deployment and consumption concepts
  • 2. Describe data preparation for AI models
  • 3. Describe model training and evaluation concepts
- Describe principles of responsible AI
  • 1. Describe transparency considerations
  • 2. Describe privacy and security considerations
  • 3. Describe inclusiveness considerations
  • 4. Describe accountability considerations
  • 5. Describe fairness considerations
  • 6. Describe reliability and safety considerations

>> Relevant AI-901 Answers <<

Pass Guaranteed Quiz 2026 AI-901: Microsoft Azure AI Fundamentals High Hit-Rate Relevant Answers

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Microsoft Azure AI Fundamentals Sample Questions (Q82-Q87):

NEW QUESTION # 82
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:
Box: a multimodal
Processing prompts that contain images requires you to deploy and use a multimodal model (such as GPT-4o) via Microsoft Foundry.
Reference:
https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/flow-process-image


NEW QUESTION # 83
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:

A schema defines which fields to extract when analyzing content.
In Azure Content Understanding, the schema or fieldSchema defines the structured data that the analyzer extracts from content, including field names, types, and extraction behavior. Microsoft documentation states that Content Understanding lets you define a schema to extract, classify, or generate field values from unstructured content.
The other options are incorrect:
A keyword list does not define the complete structured output fields.
OCR-only processing extracts text, but it does not define structured fields.
A synchronous API call describes a request pattern, not the extraction schema.


NEW QUESTION # 84
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each connect selection is worth one point.

Answer:

Explanation:

Explanation:

Statement 1: Using Azure Speech in Foundry Tools for batch transcription requires live audio input from a microphone. = No Batch transcription is used to process stored audio files, not live microphone input. Live microphone input is used for real-time speech recognition scenarios.
Statement 2: Azure Speech in Foundry Tools can analyze video frames to detect and label objects while transcribing audio. = No Azure Speech is for speech capabilities such as speech recognition, speech synthesis, and speech translation.
Detecting and labeling objects in video frames is a computer vision/video analysis capability, not an Azure Speech capability.
Statement 3: Speech translation in Azure Speech in Foundry Tools can translate spoken audio into text in another language. = Yes Speech translation converts spoken input in one language into translated text in another language.


NEW QUESTION # 85
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: B,D

Explanation:
Giving a generative AI model clear, structural instructions (commonly referred to as Prompt Engineering) is the standard method used to define its persona, guide its behavior, and place strict operational boundaries on its responses.This is typically achieved through explicit instruction sets like System Instructions and targeted Prompt Guidelines.
1. Defining the Agent's Role and BehaviorEstablishing a persona prevents the AI from wandering into areas outside its intended scope and ensures the delivery style matches your needs.
2. Defining Constraints on ResponsesConstraints act as guardrails that prevent the AI from hallucinating, rambling, or providing incorrect information.
Reference:
https://ai.google.dev/gemini-api/docs/prompting-strategies


NEW QUESTION # 86
You are explaining generative AI workflows to a colleague. What is the first step of a generative AI workflow?

Answer: A

Explanation:
Training a generative AI model using data is a foundational step in the workflow, but it is preceded by data collection and preparation. After the model is trained, subsequent steps involve validation, generation, and refinement.
Steps in a generative AI workflow
1. Data Gathering: Collect a massive, relevant dataset (images, text, audio, etc.) that will be used for training.
2. Data Preparation: Clean and preprocess the raw data. This includes removing errors, standardizing formats, and structuring the data so the model can comprehend it.
*-> 3. Model Training: Feed the prepared data into the model. During this stage, the model learns patterns and relationships within the data to understand how to create new content.
4. Model Validation: Test the model on a separate set of data to evaluate its performance and accuracy.
5. Content Generation: Use the trained and validated model to create new content based on prompts.
6. Refinement: Fine-tune the model using human feedback or additional data to improve its output and address specific tasks.
Reference:
https://www.tricension.com/domainai/proper-training-for-generative-ai/


NEW QUESTION # 87
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