Microsoft AI-901 Exam Syllabus Topics:
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Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-901
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Microsoft Azure AI Fundamentals Sample Questions:
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?
- A. temperature
- B. system instructions
- C. tokens per minute (TPM)
- D. max completion tokens
Correct Answer: B π³οΈ
Explanation: Only visible for DumpExam members. You can sign-up / login (it's free).
You have a Microsoft Foundry project that contains a generative AI model deployment.
You test the model by using the Foundry playground.
You need to develop an application that sends requests to the deployed model.
Which information must the application include to call the model?
- A. The Foundry project display name
- B. The model endpoint and authentication credentials
- C. The model training dataset
- D. The exported playground session history
Correct Answer: B π³οΈ
Explanation: Only visible for DumpExam members. You can sign-up / login (it's free).
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Statement 1: Voice Live returns only transcribed text. = No
Voice Live is not limited to transcription. Microsoft documentation states that the Voice Live API supports real-time bidirectional voice applications, including speech recognition, text-to-speech synthesis, avatar streaming, animation data, and audio processing.
Statement 2: Voice Live requires you to separately implement speech to text and text to speech services. = No Voice Live provides a single real-time voice API experience rather than requiring separate STT and TTS implementations for the conversational loop. Microsoft describes live AI voice conversations as combining speech capabilities for real-time interaction, and the Voice Live API includes speech recognition and text-to- speech synthesis features.
Statement 3: Voice Live combines speech to text, reasoning, and text to speech into a single conversational experience. = Yes This is correct. Microsoft's guidance explains that Azure OpenAI audio/realtime capabilities are for scenarios that combine audio with language understanding, reasoning, or generation in a single model call, and Voice Live supports real-time voice-enabled applications over WebSocket connections.
Select the answer that correctly complete the sentence.
Correct Answer:
Explanation:
Azure Text Analytics client library
Comprehensive and Detailed Explanation with all Azure AI documents: =
The completed sentence is:
To develop an application that analyzes text by using Azure Language in Foundry Tools, use the Azure Text Analytics client library package.
Azure AI Language text analysis features, such as sentiment analysis, named entity recognition, key phrase extraction, language detection, and text summarization, are accessed in code by using the Azure Text Analytics client library.
The other options are incorrect:
Azure AI Projects client library is used for Foundry project and agent-related workflows, not specifically Azure Language text analysis.
Azure OpenAI client library is used to call OpenAI model deployments, not Azure Language text analytics APIs.
Azure Speech SDK is used for speech-to-text and text-to-speech workloads, not text analysis.
Select the answer that correctly completes the sentence.
Correct Answer:
Explanation:
Ongoing monitoring, feedback, and evaluation are goals of the Reliability & Safety principle.
The Microsoft responsible AI principle of Reliability and safety focuses on ensuring that AI systems operate consistently, safely, and as intended across different conditions. This includes testing, monitoring, collecting feedback, and evaluating system performance over time.
Why the other options are incorrect:
Human oversight and control aligns more closely with accountability.
Data governance and management aligns more closely with privacy and security.
The minimization of stereotyping, demeaning, and erasing outputs aligns more closely with fairness and inclusiveness.
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