Itcertkr AB-100 최신 PDF 버전 시험 문제집을 무료로 Google Drive에서 다운로드하세요: https://drive.google.com/open?id=1J-im1Fi9-JgqD6Cpc32pTkG9Cl1fr3Ol
Microsoft인증 AB-100덤프로Microsoft시험을 패스,하지 못하셨다구요? 최선을 다했는데도 실패하였다는 말은 영원히 하지마세요. Microsoft인증 AB-100시험을 패스하는 방법은 많고도 많습니다. Itcertkr의Microsoft인증 AB-100덤프로 시험에 다시 도전해보세요. Itcertkr의Microsoft인증 AB-100덤프는 착한 가격에 100%에 달하는 적중율과 패스율을 보장해드립니다. 시험에서 불합격성적표를 받으시면 덤프구매시 지불한 덤프비용을 환불처리해드립니다. Itcertkr의Microsoft인증 AB-100덤프로 시험패스를 꿈꿔보세요.
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목표가 있다면 목표를 향해 끊임없이 달려야 멋진 인생이 됩니다. 지금의 현황에 만족하여 아무런 노력도 하지 않는다면 언젠가는 치열한 경쟁을 이겨내지 못하게 될것입니다. IT업종에 종사중이시라면 다른분들이 모두 취득하는 자격증쯤은 마련해야 되지 않겠습니까? Microsoft인증 AB-100시험은 요즘 가장 인기있는 자격증 시험의 한과목입니다. IT업계에서 살아남으려면Itcertkr에서Microsoft인증 AB-100덤프를 마련하여 자격증에 도전하여 자기의 자리를 찾아보세요.
질문 # 86
Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
A company uses Microsoft 365 and Dynamics 365.
You need to recommend a solution to automatically summarize email threads, generate suggested replies in Microsoft Outlook, and provide meeting preparation summaries that include relevant customer relationship management (CRM) data.
Solution: You recommend Microsoft 365 Copilot for Sales.
Does this meet the goal?
정답：A
설명：
Correct:
* You recommend Microsoft 365 Copilot for Sales.
Incorrect:
* You recommend a classic Microsoft Dataverse workflow.
* You recommend a Microsoft 365 Copilot agent template.
Note:
In the described scenario, Microsoft 365 Copilot for Sales acts as the primary bridge between your productivity tools and CRM data. It integrates directly into Microsoft Outlook and Teams to surface real-time insights from Dynamics 365 Sales or Salesforce.
Key capabilities for this specific workflow include:
Automated Email Summarization: Copilot scans long email threads in Outlook to extract key points, highlights, and BANT (Budget, Authority, Need, Timeline) data. If the sender is an external contact recognized in your CRM, the summary is automatically enriched with relevant account and opportunity data.
Suggested Email Replies: When replying to customer emails, Copilot generates drafts based on the context of the conversation and existing CRM data. You can use predefined response categories (e.g., "Reply to an inquiry," "Offer a proposal") or custom prompts to include specific opportunity details in the draft.
Meeting Preparation Summaries: Before a scheduled meeting, Copilot for Sales provides a
"preparation card" in Teams or Outlook. This summary includes:
- CRM Data: Matched opportunity and account attributes.
- Contextual History: Summaries of past email exchanges and the last three seller notes.
- Strategic Insights: Key risks, follow-up actions, and discussion points from previous interactions.
Reference:
https://msdynamicsworld.com/blog/microsoft-copilot-sales-close-deals-faster-ai
질문 # 87
A company has a Microsoft Foundry generative Al model.
You need to evaluate the model ' s output to measure the overall quality and coherence of generated responses. The evaluation must use GPT-4o as a judge and return a numeric score for each output.
Which type of metric should you use?
정답：A
질문 # 88
Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
Your organization creates a new AI Center of Excellence (CoE) to guide enterprise-wide adoption of generative AI. A project team submits a proposal requesting immediate development of a generative AI model. They argue that identifying use cases and validating data quality can wait until after the prototype is built, since the CoE can "fix the data later." You are asked whether this approach aligns with Microsoft's recommended AI adoption lifecycle, which starts with identifying use cases, selecting domain-specific data, preparing and validating that data, designing and training solutions, and then monitoring and adapting them over time.
According to Microsoft's AI adoption guidance, is it appropriate to skip identifying use cases and validating domain-specific data before beginning AI model development?
정답：B
설명：
Microsoft's generative AI adoption framework - as shown in the diagram - emphasizes a sequenced lifecycle:
Identify use cases
Prepare, validate, and aggregate the required data
Design, train, and validate AI solutions
Monitor and adapt
The Microsoft Learn module clearly states that a Center of Excellence ensures organizations start with aligned business use cases and validated domain-specific data before any model development begins.
Skipping these early steps introduces high risk, creates misaligned solutions, and prevents effective contextualization of AI models.
Therefore, beginning model development without first identifying use cases and validating data does not follow Microsoft's recommended AI planning and adoption process.
References:
https://learn.microsoft.com/en-us/training/modules/intro-ai-center-excellence/2-how-center- excellence-assists-planning-adoption-generative-ai
https://learn.microsoft.com/en-us/training/modules/intro-ai-center-excellence/1-introduction- generative-ai-center-excellence
https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/center-of- excellence
질문 # 89
A company uses a fine-tuned Microsoft Foundry model that requires frequent updates as new customer feedback becomes available.
You need to design an application lifecycle management (ALM) process that meets the following requirements:
- Data changes must be tracked and versioned.
- The model must be retrained consistently by using approved training
data.
Which two actions should you include in the design? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
정답：C,E
설명：
To implement a new Application Lifecycle Management (ALM) process for your fine-tuned Microsoft Foundry model, you can leverage Azure Blob Storage for raw data versioning and Azure AI Foundry (formerly Azure AI Studio) for managed data assets and model retraining.
1. Data Tracking and Versioning in Azure Blob Storage
Enable blob versioning to automatically maintain a history of your training data.
Enable Versioning: In the Azure portal, navigate to your storage account under Data management > Data protection and select Enable versioning for blobs.
Immutable Tracking: This ensures that every update to a training file creates a new version, allowing you to restore or reference specific historical states of your dataset for auditability.
2. Uploading and Managing Data in Microsoft Foundry
Integrate your versioned blob storage with Microsoft Foundry to create "Data assets" that the model can use for retraining.
Reference:
https://learn.microsoft.com/en-us/azure/storage/blobs/versioning-enable
https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/data-add?view=foundry-classic
질문 # 90
A company has an Al solution named Solution1 that is deployed to the production environment.
Solution! uses an Azure OpenAI model to generate marketing emails for existing customers.
During an internal review, you identify that Solution1 creates different emails depending on the customers' traits.
You need to recommend a strategy to mitigate the bias. The strategy must adhere to Microsoft responsible Al principles.
What should you recommend?
정답：B
설명：
The scenario describes a deployed AI solution using Azure OpenAI that exhibits bias (creating disparate outcomes based on customer traits). This directly impacts the Fairness principle of Microsoft's Responsible AI framework.
Why "Modify the system instructions" is the Correct Strategy:
Direct Control via System Metaprompts: In large language model (LLM) applications like those powered by Azure OpenAI, the system instructions (or system message) define the behavior, constraints, and tone of the model. By modifying these instructions, you can explicitly direct the model to treat all customer segments equitably and ignore specific sensitive traits when drafting marketing content.
질문 # 91
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Itcertkr는 고객님의 IT자격증취득의 작은 소원을 이루어지게 도워드리는 IT인증시험덤프를 제공해드리는 전문적인 사이트입니다. Itcertkr 표 Microsoft인증AB-100시험덤프가 있으면 인증시험걱정을 버리셔도 됩니다. Itcertkr 표 Microsoft인증AB-100덤프는 시험출제 예상문제를 정리해둔 실제시험문제에 가장 가까운 시험준비공부자료로서 공을 들이지않고도 시험패스가 가능합니다.
AB-100완벽한 시험자료: https://www.itcertkr.com/AB-100_exam.html
그리고 Itcertkr AB-100 시험 문제집의 전체 버전을 클라우드 저장소에서 다운로드할 수 있습니다: https://drive.google.com/open?id=1J-im1Fi9-JgqD6Cpc32pTkG9Cl1fr3Ol