Our AI-901 guide questions have helped many people obtain an international certificate. In this industry, our products are in a leading position in all aspects. If you really want to get an international certificate, our AI-901 training quiz is really your best choice. Of course, you really must get international certification if you want to stand out in the job market and get better jobs and higher salaries. With the help of our AI-901 Exam Materials, you can reach your dream.
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
| Exam Number: | AI-900 |
| Available Languages: | Chinese (Traditional), English, Portuguese (Brazil), Japanese, German, Korean, French, Chinese (Simplified), Spanish |
| Passing Score: | 700 (out of 1000) |
| Exam Duration: | 60 minutes |
| Certificate Validity Period: | Does not expire (Fundamentals certification) |
| Exam Price: | Approx. 99 USD (varies by region) |
| Related Certifications: | Microsoft Azure Fundamentals (AZ-900) Microsoft Azure Data Fundamentals (DP-900) |
| Real Exam Qty: | 40-60 |
| Exam Format: | Case study (limited), Multiple choice, Drag and drop, Multiple response |
| Recommended Training: | Microsoft Learn - AI-900 Learning Path Azure AI Fundamentals Course |
| Exam Registration: | Schedule exam via Pearson VUE Microsoft Certification Portal |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online proctored exam or in-person test center |
| Pre Condition: | No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/ |
TestSimulate exam study material is essential for candidates who want to appear for the Microsoft AI-901 certification exams and clear it to validate their skill set. This preparation material comes with Up To 1 year OF Free Updates And Free Demos. Place your order now and get Real AI-901 Exam Questions with these offers.
| Topic | Details |
|---|---|
| Topic 1 |
|
| Topic 2 |
|
NEW QUESTION # 39
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Box: the Azure Language MCP server
To enable an AI agent in Microsoft Foundry to utilize Azure Language capabilities for text analysis, you must configure the Azure Language Model Context Protocol (MCP) server.
Microsoft Foundry integrates its ecosystem of deterministic AI services through the standardized Model Context Protocol (MCP). This removes the need to write custom routing logic or stitch together multiple standalone APIs.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/language-service/overview
NEW QUESTION # 40
You have a Microsoft Foundry project that contains a vision-enabled model deployment.
You need to develop an application that sends a message containing text and an image URL.
The solution must ensure the quickest response time.
Which message structure should you include in the request?
Answer: A
Explanation:
To achieve the fastest possible response time in Microsoft Foundry/Azure AI, you must combine the text prompt and image URL into a single user message, utilizing a system message for instructions, and opting for a low-latency model like gpt-4o-mini.
Sending separate requests or splitting the text and image into different messages increases network overhead and conversation context length, both of which add unnecessary latency.
Note:
1. Required Message Structure
You should include both a system message and a custom user message in your API request payload:
System Message: Use this to define the context, guardrails, and explicit format requirements. It sets up the model behavior before the image is even processed, optimizing processing efficiency.
User Message (Custom Message): This is where you pass your text prompt and the actual image reference.
2. Request Handling: Single vs. Separate Requests
You must send the text item and the image item in the same single request.
Reference:
https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/transitioning-from-azure-language-features-to-foundry-models/4524092
NEW QUESTION # 41
You are developing an application that extracts fields from PDFs by using Azure Content Understanding in Foundry Tools.
You need to use the Python SDK to submit a PDF for analysis and retrieve the extraction results.
What should you do?
Answer: D
Explanation:
Azure Content Understanding analysis operations are long-running operations in the Python SDK. Microsoft's Python SDK documentation states that analysis operations return a poller, and the SDK provides LROPoller types that handle polling automatically when you call .result().
Therefore, the correct workflow is to submit the PDF by calling begin_analyze(), receive a poller, and then call:
result = poller.result()
Option B is incorrect because extraction results are not read from request headers.
Option C is incorrect because the requirement is to use Azure Content Understanding extraction, not build a manual OCR-only mapping pipeline.
Option D is incorrect because the SDK analysis pattern is asynchronous/long-running, not a simple synchronous analyze() call that returns all extracted fields in the same request.
NEW QUESTION # 42
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
Explanation:
To compare the costs, capabilities, and performance of large language models (LLMs) in the Foundry portal, you should use the Model leaderboard.
Why Use the Model Leaderboard
The leaderboard allows you to:
Compare models side-by-side: Evaluate multiple LLMs simultaneously for trade-offs regarding estimated costs, throughput, safety, and quality.
Make informed decisions: Select the most cost-effective model for specific workloads before committing to deployments, reducing the risk of expensive errors or overspending.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/concepts/manage-costs
NEW QUESTION # 43
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: D
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 # 44
......
Reliable AI-901 Exam Book: https://www.testsimulate.com/AI-901-study-materials.html