AI-901인증덤프샘플체험최신시험기출문제와예상문제모음자료

Itexamdump의 Microsoft인증 AI-901덤프의 무료샘플을 이미 체험해보셨죠? Itexamdump의 Microsoft인증 AI-901덤프에 단번에 신뢰가 생겨 남은 문제도 공부해보고 싶지 않나요? Itexamdump는 고객님들의 시험부담을 덜어드리기 위해 가벼운 가격으로 덤프를 제공해드립니다. Itexamdump의 Microsoft인증 AI-901로 시험패스하다 더욱 넓고 좋은곳으로 고고싱 하세요.

Microsoft AI-901 시험요강:

주제소개
주제 1
  • 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.
주제 2
  • 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.

>> AI-901인증덤프 샘플체험 <<

AI-901인증공부문제 & AI-901자격증참고서

연구결과에 의하면Microsoft인증 AI-901시험은 너무 어려워 시험패스율이 낮다고 합니다. Itexamdump의 Microsoft인증 AI-901덤프와 만나면Microsoft인증 AI-901시험에 두려움을 느끼지 않으셔도 됩니다. Itexamdump의 Microsoft인증 AI-901덤프는 엘리트한 IT전문가들이 실제시험을 연구하여 정리해둔 퍼펙트한 시험대비 공부자료입니다. 저희 덤프만 공부하시면 시간도 절약하고 가격도 친근하며 시험준비로 인한 여러방면의 스트레스를 적게 받아Microsoft인증 AI-901시험패스가 한결 쉬워집니다.

최신 Microsoft Certified: Azure AI Fundamentals AI-901 무료샘플문제 (Q95-Q100):

질문 # 95
Hotspot Question
Select the answer that correctly completes the sentence.

정답：

설명：

Explanation:
Box: the Azure Language MCP server
To enable an AI agent in Microsoft Foundry to utilize Azure Language capabilities for text analysis, you must configure the Azure Language Model Context Protocol (MCP) server.
Microsoft Foundry integrates its ecosystem of deterministic AI services through the standardized Model Context Protocol (MCP). This removes the need to write custom routing logic or stitch together multiple standalone APIs.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/language-service/overview


질문 # 96
You are developing an application that will coordinate a travel-booking workflow by gathering user preferences, searching for options, requesting approval, and booking services. The solution will maintain context across the steps.
Which type of Al workload is this an example of?

정답：A

설명：
The described solution coordinates a multi-step workflow : gathering user preferences, searching for options, requesting approval, booking services, and maintaining context across steps. This is an example of Agentic AI
.
Agentic AI systems use AI agents to reason over user goals, maintain context, decide which actions to take, and use tools or services to complete tasks across multiple steps.
Why the other options are incorrect:
A). information extraction extracts structured data from content.
C). computer vision analyzes images or video.
D). generative AI creates new content, but the scenario specifically describes an autonomous, context-aware workflow with actions, which is Agentic AI .


질문 # 97
Select the answer that correctly complete the sentence.

정답：

설명：

Explanation:

The completed sentence is:
Information extraction solutions that detect and read text in scanned documents and images rely on computer vision .
Detecting and reading text in scanned documents and images is typically done with OCR , which is a computer vision capability. Microsoft describes OCR as text recognition/text extraction that extracts printed or handwritten text from images and documents.


질문 # 98
What should you use to identify similar faces in a set of images?

정답：D

설명：
To identify similar faces across different images using Azure, the Azure AI Face service is the most suitable choice. This service leverages AI algorithms to detect, recognize, and analyze human faces, including features like face grouping based on visual similarity.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/find-similar-faces


질문 # 99
You plan to create an AI application that will use Azure OpenAI Service. The solution requires that a specific amount of throughput be allocated. Which type of deployment should you use?

정답：A

설명：
When a specific amount of throughput is needed with Azure OpenAI Service, you should use Provisioned Throughput Units (PTUs) for your deployment. PTUs allow you to reserve a fixed amount of processing capacity for your models, ensuring consistent performance and avoiding potential throttling or rate limits.
In contrast, the "Standard" deployment option in Azure OpenAI Service uses a "pay-as-you-go" model, where you are billed for the amount of usage. While this can be suitable for applications with fluctuating usage patterns, it does not provide the same level of throughput control as PTUs.
In summary: When you need to allocate a specific amount of throughput with Azure OpenAI Service, choose the "Provisioned" deployment type, which allows you to use PTUs.
Reference:
https://github.com/MicrosoftDocs/azure-ai-docs/blob/main/articles/ai-services/openai/concepts/provisioned-throughput.md


질문 # 100
......

최근들어 Microsoft AI-901시험이 큰 인기몰이를 하고 있는 가장 핫한 IT인증시험입니다. Microsoft AI-901덤프는Microsoft AI-901시험 최근문제를 해석한 기출문제 모음집으로서 시험패스가 한결 쉬워지도록 도와드리는 최고의 자료입니다. Microsoft AI-901인증시험을 패스하여 자격증을 취득하면 보다 쉽고 빠르게 승진할수 있고 연봉인상에도 많은 도움을 얻을수 있습니다.

AI-901인증공부문제: https://www.itexamdump.com/AI-901.html