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Microsoft AI-901 Exam Overview:
| Certification Vendor: | Microsoft |
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| Exam Name: | Microsoft Azure AI Fundamentals (AI-900) Exam |
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| Exam Number: | AI-900 |
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| Real Exam Qty: | 40-60 |
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| Exam Duration: | 60 minutes |
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| Available Languages: | Spanish, Korean, French, Portuguese (Brazil), Chinese (Simplified), English, Japanese, German, Chinese (Traditional) |
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| Certificate Validity Period: | Does not expire (Fundamentals certification) |
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| Exam Price: | Approx. 99 USD (varies by region) |
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| Passing Score: | 700 (out of 1000) |
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| Exam Format: | Drag and drop, Case study (limited), Multiple choice, Multiple response |
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| Related Certifications: | Microsoft Azure Fundamentals (AZ-900) Microsoft Azure Data Fundamentals (DP-900) |
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| Recommended Training: | Azure AI Fundamentals Course Microsoft Learn - AI-900 Learning Path |
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| Exam Registration: | Schedule exam via Pearson VUE Microsoft Certification Portal |
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| Sample Questions: | Microsoft AI-901 Sample Questions |
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| Exam Way: | Online proctored exam or in-person test center |
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| Pre Condition: | No formal prerequisites required. Basic understanding of cloud computing and AI concepts is recommended. |
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| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/ |
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| Topic | Details |
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| Topic 1 | - Implement AI solutions by using Microsoft Foundry: This domain is hands-on and focuses on building and deploying AI solutions using the Microsoft Foundry platform and its associated tools. It spans generative AI apps, text and speech processing, computer vision, and document intelligence all implemented through the Foundry portal and SDK.
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| Topic 2 | - Identify AI concepts and capabilities: This domain covers the foundational knowledge of AI from ethical principles and responsible design to understanding how AI models work and what kinds of tasks they can perform. It also explores the full range of AI workloads including generative AI, computer vision, speech, and information extraction.
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Microsoft Azure AI Fundamentals Sample Questions (Q35-Q40):
NEW QUESTION # 35
Hotspot Question
Select the answer that correctly complete the sentence.

Answer:
Explanation:

NEW QUESTION # 36
You have a Microsoft Foundry project named project1 that contains an Azure OpenAI resource named Resource1.
To Resource1, you deploy a gpt-4.1-mini model by using a model deployment named my-mini-gpt.
You need to connect to my-mini-gpt from an application.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

NEW QUESTION # 37
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:
Explanation:

NEW QUESTION # 38
In the Microsoft Foundry portal, you create an agent named Agent1, and then deploy the agent.
You open the Foundry playground to test Agent1.
What does the playground use to ensure that the tests reflect production behavior?
- A. the model's base behavior without any agent instructions or tools
- B. the configuration of Agent1
- C. the last saved configuration draft that was NOT deployed
- D. a default configuration generated by the playground
Answer: B
Explanation:
The Configuration of the Agent: When you open the playground for a deployed agent in the Microsoft Foundry portal, it connects directly to the active deployment and uses the actual configuration, version, model, and tool bindings of the deployed agent to mirror real production logic.
Reference:
https://learn.microsoft.com/en-us/answers/questions/5564123/how-to-enable-the-agents-playground-feature-in-azu
NEW QUESTION # 39
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: Generating a response to a user prompt occurs during the inference stage. = Yes When a deployed generative AI model receives a user prompt and generates an output, that process is called inference . The model is being used to produce a response, not being trained.
Statement 2: A generative AI model generates responses by copying stored documents directly from the model's training data. = No Generative AI models do not normally respond by simply copying stored documents from training data. They generate outputs based on learned statistical patterns. In some cases, models may reproduce memorized content, but that is not the normal or intended generation mechanism.
Statement 3: A generative AI model produces output by predicting the next token based on patterns learned from the model's training data. = Yes This is correct. Large language models generate text by predicting likely next tokens based on the prompt and learned patterns from training.
NEW QUESTION # 40
......
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