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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Azure AI Fundamentals |
| Exam Number: | AI-900 |
| Passing Score: | 700 / 1000 |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals |
| Certificate Validity Period: | 1 year (renewable via free online assessment on Microsoft Learn) |
| Exam Price: | USD 99 |
| Available Languages: | German, Spanish, Portuguese (Brazil), Korean, Russian, Arabic (Saudi Arabia), Italian, Japanese, Chinese (Traditional), Indonesian (Indonesia), English, Chinese (Simplified), French |
| Exam Duration: | 45-60 |
| Real Exam Qty: | 40-60 |
| Exam Format: | Drag and drop, Match the service to use case, Multiple choice, Multiple select, Scenario-based |
| 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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| Thema | Einzelheiten |
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| Thema 1 |
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| Thema 2 |
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48. Frage
You have a Microsoft Foundry project that has a generative AI model deployment.
You need to ensure that responses generated by the model minimize costs and remain within a defined length.
Which parameter should you configure?
Antwort: A
Begründung:
The Max Completion Tokens (or max_tokens / max_output_tokens in the API) parameter is exactly the tool you use to enforce a fixed length on AI-generated responses and keep costs predictable.
How the Parameter Works
What it does: It sets a strict upper bound on the number of output tokens the model can generate for your completion. Once this number is reached, the model will stop generating (cut off) regardless of whether it finished its thought.
What it doesn't do: It does not set a minimum length or force the model to write exactly that amount. It only acts as a ceiling.
Reference:
https://learn.microsoft.com/en-us/answers/questions/5828812/reasoning-models-like-5-1-fails-with-500-error-cod
49. Frage
Select the answer that correctly completes the sentence.
Antwort:
Begründung:
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.
50. Frage
Which Azure OpenAI model should you use to summarize the text from a document?
Antwort: B
Begründung:
You can use ChatGPT to summarize text. This can help you understand complex information more easily, summarize the central argument of your own paper, or clarify your research question.
Reference:
https://community.openai.com/t/information-summary-by-using-api/578792
51. Frage
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?
Antwort: D
Begründung:
For a vision-enabled model, Microsoft documentation shows that multimodal prompts can include both text and image content in the same user message content array. Azure OpenAI vision models accept multimodal image-and-text input and return natural language responses.
The correct request structure is a user message with a content array containing both items, for example:
{
"role": "user",
"content": [
{"type": "input_text", "text": "What is in this image?"},
{"type": "input_image", "image_url": image_url}
]
}
This avoids sending separate requests and is therefore the best choice for quickest response time.
A and C are incorrect because they send the text and image separately.
B is incorrect because the image/question should be sent as a user message, while system messages are used for instructions and behavior.
52. Frage
Select the answer that correctly completes the sentence.
Antwort:
Begründung:
Explanation:
Evaluating model outcomes across demographic groups to reduce bias is an example of the Microsoft responsible AI principle of fairness.
The Microsoft responsible AI principle of fairness means AI systems should treat all people fairly and avoid unfair bias or discrimination across groups.
The other options are incorrect:
accountability means people and organizations remain responsible for AI systems and their effects.
privacy and security focuses on protecting data and controlling access.
transparency means users should understand when and how AI is being used, including system capabilities and limitations.
53. Frage
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