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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identify AI concepts and responsibilities | 40-45% | - Identify AI concepts and features
|
| Topic 2: Implement AI solutions by using Microsoft Foundry | 55-60% | - Get started with Microsoft Foundry
|
>> Detailed AI-901 Study Dumps <<
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NEW QUESTION # 33
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: Evaluators in Microsoft Foundry replace the need for configuring token limits. = No Evaluators are used to assess model or agent output quality, safety, and reliability. They do not replace model configuration settings such as token limits. Microsoft describes evaluators as tools that measure the quality, safety, and reliability of AI responses.
Statement 2: Evaluators in Microsoft Foundry can assess the quality and safety of responses generated by a generative AI model. = Yes This is correct. Microsoft Foundry includes built-in evaluators for general quality metrics such as coherence and fluency, safety/security metrics, RAG metrics, and agent-specific metrics.
Statement 3: Evaluators in Microsoft Foundry can retrain a deployed generative AI model automatically when quality issues are detected. = No Evaluators measure and report quality, safety, and reliability issues. They do not automatically retrain deployed generative AI models. Microsoft describes evaluation as measuring model or agent performance against test data, while monitoring can alert when outputs fail quality thresholds.
NEW QUESTION # 34
You deploy an AI system to assist with hiring decisions.
Company policy requires that human reviewers oversee AI-generated recommendations and remain responsible for final hiring decisions.
Which Microsoft responsible AI principle is this an example of?
Answer: C
Explanation:
Accountability is the Microsoft responsible AI principle that ensures human oversight so that people remain responsible for AI-driven decisions.
Human Oversight: Requiring human review ensures that AI operates under effective governance rather than acting autonomously on high-impact choices.
Final Authority: Keeping humans legally and operationally responsible prevents automated systems from dictating critical outcomes like hiring.
Reference:
https://www.microsoft.com/en-us/ai/principles-and-approach
NEW QUESTION # 35
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 36
Drag and Drop Question
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
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 # 38
......
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