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Microsoft AI-901 Exam Overview:

Certification Vendor:Microsoft
Exam Name:Microsoft Azure AI Fundamentals
Exam Number:AI-901
Passing Score:700
Certificate Validity Period:Lifetime
Real Exam Qty:30-40
Available Languages:Arabic (Saudi Arabia), Russian, English, Japanese, German, Portuguese (Brazil), Chinese (Simplified), Spanish, French, Korean, Indonesian (Indonesia), Italian, Chinese (Traditional)
Exam Price:$99 USD
Exam Format:Multiple select, Case studies, Multiple choice
Exam Duration:60 minutes
Recommended Training:Microsoft Learn: AI concepts for developers and technology professionals
Microsoft Learn: Get started with Microsoft Foundry
Exam Registration:Pearson VUE Scheduling
Microsoft Certification Exam Registration
Sample Questions:Microsoft AI-901 Sample Questions
Exam Way:Online proctored or onsite at Pearson VUE test centers
Pre Condition:No required prerequisites; basic understanding of cloud computing and familiarity with Python syntax recommended
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-901/

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Microsoft AI-901 Exam Syllabus Topics:

TopicDetails
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.
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.

Microsoft Azure AI Fundamentals Sample Questions (Q74-Q79):

NEW QUESTION # 74
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: A

Explanation:
For a vision-enabled GPT model deployment, use the Azure OpenAI Responses API to send text and image inputs in a single request. Microsoft's Foundry SDK documentation states that the endpoint exposes the Responses API and provides access to Azure OpenAI models, including chat completions and multimodal- capable model interactions.


NEW QUESTION # 75
You are developing an application that processes voicemail recordings by using Azure Content Understanding in Foundry Tools.
Which feature does Azure Content Understanding use to convert audio to text?

Answer: D

Explanation:
Azure Content Understanding uses transcription to convert audio content, such as voicemail recordings, into text. Microsoft's Azure Content Understanding audio documentation states that transcription converts conversational audio into searchable and analyzable text-based transcripts.
Option A. Voice Live is not the feature used by Content Understanding to convert voicemail recordings into text.
Option B. key phrase extraction identifies important phrases after text is available; it is not the audio-to-text conversion step.
Option D. optical character recognition (OCR) is for extracting text from images or documents, not audio.
Therefore, the correct answer is C. transcription.


NEW QUESTION # 76
You deploy the Azure OpenAI service to generate images.
You need to ensure that the service provides the highest level of protection against harmful content.
What should you do?

Answer: A

Explanation:
Azure OpenAI, Content filtering
Azure OpenAI includes a content filtering system that works alongside core models, including image generation models. This system works by running both the prompt and completion through a set of classification models designed to detect and prevent the output of harmful content.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/content-filter


NEW QUESTION # 77
You need to build an AI solution that generates marketing email drafts based on a short description of a product and its target audience. Which AI workload should you use?

Answer: C

Explanation:
Generating marketing email drafts from a short product description and target audience is a content generation task. This is a generative AI workload because the system creates new text based on the user's prompt.


NEW QUESTION # 78
Which natural language processing feature can be used to identify the main talking points in customer feedback surveys?

Answer: C

Explanation:
To identify main talking points in feedback using Azure natural language processing, the Key Phrase Extraction feature within the Azure AI Language service is the most appropriate choice.
This feature analyzes text and extracts the most relevant and important phrases, effectively highlighting the core topics or themes present in the feedback.
Reference:
https://learn.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing


NEW QUESTION # 79
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