AI-901 - High-quality Microsoft Azure AI Fundamentals Instant Download

2026 Latest PassExamDumps AI-901 PDF Dumps and AI-901 Exam Engine Free Share: https://drive.google.com/open?id=1Zi0dKWOnRGW_9FMQVU4X0bK95tBDXarF

We have created a number of reports and learning functions for evaluating your proficiency for the AI-901 exam dumps. In preparation, you can optimize Microsoft AI-901 practice exam time and question type by utilizing our Microsoft AI-901 Practice Test software. PassExamDumps makes it easy to download Microsoft Azure AI Fundamentals (AI-901) exam questions immediately after purchase.

Microsoft AI-901 Exam Syllabus Topics:

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

>> AI-901 Instant Download <<

Accurate Microsoft AI-901 Study Material | AI-901 Latest Practice Questions

A good brand is not a cheap product, but a brand that goes well beyond its users' expectations. The value of a brand is that the AI-901 study materials are more than just exam preparation tool -- it should be part of our lives, into our daily lives. Do this, therefore, our AI-901 Study Materials has become the industry well-known brands, but even so, we have never stopped the pace of progress, we have been constantly updated the AI-901 study materials.

Microsoft Azure AI Fundamentals Sample Questions (Q50-Q55):

NEW QUESTION # 50
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: B,C

Explanation:
Images can be sent to these models either by passing a publicly accessible image URL or by sending Base64-encoded image data directly in the message payload.
Reference:
https://learn.microsoft.com/en-us/azure/foundry-classic/foundry-models/how-to/use-chat-multi-modal


NEW QUESTION # 51
You need to create an AI agent in Microsoft Foundry that follows a specific role and behavior when responding to users.
What should you configure?

Answer: C

Explanation:
To create an AI agent that follows a specific role and behavior, you configure system instructions . Microsoft Foundry Agent Service documentation states that agent instructions define goals, constraints, and behavior
.
Option A. tokens per minute (TPM) controls throughput quota, not behavior.
Option C. temperature controls response randomness/creativity, not the agent's role.
Option D. max completion tokens controls response length, not the agent's role or behavioral rules.
Therefore, the correct answer is B. system instructions .


NEW QUESTION # 52
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:

The completed sentence is:
To define an agent ' s role and behaviors, you must configure a system prompt for the agent.
In Microsoft Foundry / Azure AI agent scenarios, the system prompt , also referred to as system instructions
, defines how the agent should behave, what role it should follow, and what constraints it must observe.
The other options are incorrect:
deployment slot relates to hosting/deployment routing, not agent behavior.
embedding index is used for vector search or retrieval scenarios, not defining the agent's role.
fine tuning job changes or adapts model behavior through training, but it is not the standard configuration used to define an agent's role and behavior at runtime.
Therefore, the correct answer is system prompt .


NEW QUESTION # 53
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:
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 workloads include capabilities such as sentiment analysis, key phrase extraction, named entity recognition, language detection, and other text analytics features. In application code, these text analysis capabilities are accessed by using the Azure Text Analytics client library .
The other options are incorrect:
Azure AI Projects client library is used for Foundry project and agent-related development.
Azure OpenAI client library is used to call Azure OpenAI model deployments.
Azure Speech SDK is used for speech recognition, speech synthesis, and other speech workloads.


NEW QUESTION # 54
What are two types of generative Al models? Each correct answer presents a complete solution.
NOTE: Each correct answer is worth one point.

Answer: D,E

Explanation:
GPT and DALL-E are examples of generative AI model types/families.
GPT models generate natural language text, such as answers, summaries, emails, and conversations.
DALL-E models generate images from text descriptions.
Why the other options are incorrect:
A). transformer is a model architecture, not the best answer here as a generative model type/family.
B). computer vision is an AI workload area.
E). natural language processing is an AI workload area, not a specific generative AI model type.


NEW QUESTION # 55
......

Evaluate your own mistakes each time you attempt the desktop Microsoft Azure AI Fundamentals (AI-901) practice exam. It expertly is designed AI-901 practice test software supervised by a team of professionals. There is 24/7 customer service to help you in any situation. You can customize your desired AI-901 Exam conditions like exam length and the number of questions.

Accurate AI-901 Study Material: https://www.passexamdumps.com/AI-901-valid-exam-dumps.html

P.S. Free & New AI-901 dumps are available on Google Drive shared by PassExamDumps: https://drive.google.com/open?id=1Zi0dKWOnRGW_9FMQVU4X0bK95tBDXarF