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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals |
| Exam Price: | USD 99 |
| Passing Score: | 700 / 1000 |
| Real Exam Qty: | 40-60 |
| Exam Duration: | 45-60 |
| Certificate Validity Period: | 1 year (renewable via free online assessment on Microsoft Learn) |
| Available Languages: | Italian, Spanish, Chinese (Simplified), German, Korean, English, Chinese (Traditional), Russian, Portuguese (Brazil), Arabic (Saudi Arabia), Indonesian (Indonesia), Japanese, French |
| Exam Format: | Multiple choice, Scenario-based, Match the service to use case, Drag and drop, Multiple select |
| Sample Questions: | Microsoft AI-901 Sample Questions |
| Exam Way: | Online (remote proctored via Pearson VUE) or at a Pearson VUE test center |
| Pre Condition: | No prerequisites. This exam is intended for both technical and non-technical backgrounds. Data science and software engineering experience are not required. Awareness of basic cloud concepts and client-server applications is beneficial. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-900 |
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NEW QUESTION # 128
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: B
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 # 129
You have a Microsoft Foundry project that contains a vision-enabled GPT model deployment.
You need to develop an application that sends an image and a text question to the model in a single request.
What should you use?
Answer: B
Explanation:
To send an image and a text question to a vision-enabled GPT model deployment within a Microsoft Foundry project in a single request, you should target the Azure OpenAI Responses API via your Foundry Project Endpoint.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/openai/how-to/gpt-with-vision
NEW QUESTION # 130
You plan to deploy a generative AI model to a Microsoft Foundry project in the East US Azure region. What should you check first?
Answer: D
Explanation:
Model availability should be checked first. You must confirm that the specific generative AI model is supported and offered in the East US region before checking your token rate limits or allocation quota, as a model cannot be deployed in a region where it does not exist.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/foundry-models/quotas-limits
NEW QUESTION # 131
Which Azure AI Foundry Service can be used to identify documents that contain sensitive information?
Answer: A
Explanation:
Azure AI Language can be used to identify documents containing sensitive information through its Personally Identifiable Information (PII) detection feature, which uses Named Entity Recognition (NER) to detect and categorize data like names, addresses, phone numbers, and financial details within unstructured text and native documents. This feature classifies sensitive data into predefined categories and can also redact the identified information, replacing it with asterisks to protect privacy.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable- information/overview
NEW QUESTION # 132
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement 1: Azure Content Understanding in Foundry Tools can analyze only PDF documents. = No Azure Content Understanding is not limited to PDF documents. It can analyze different content types, including documents, forms, images, audio, and video.
Statement 2: Azure Content Understanding in Foundry Tools results are returned in the JSON format.
= Yes
Azure Content Understanding returns structured analysis output in JSON format.
Statement 3: Azure Content Understanding in Foundry Tools can extract structured fields from documents and forms. = Yes Azure Content Understanding can extract structured fields from documents and forms by using analyzers and schemas.
NEW QUESTION # 133
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