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| Section | Weight | Objectives |
|---|---|---|
| Identify an implementation and adoption strategy for Microsoft's AI apps and services | 20-25% | - Align an AI strategy with Microsoft responsible AI policies
|
| Identify benefits, capabilities, and opportunities for Microsoft's AI apps and services | 35-40% | - Identify benefits and capabilities of Microsoft 365 Copilot and Microsoft Copilot
|
| Identify the business value of generative AI solutions | 35-40% | - Identify benefits and capabilities of generative AI solutions
|
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NEW QUESTION # 95
- 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:
Answer Area
* Using incomplete or poor-quality data during generative AI model training can increase costs. Answer:
Yes
* AI models rely on training data to learn patterns and identify relationships to produce outputs. Answer:
Yes
* Generative AI models trained on non-representative datasets can produce inaccurate or unbalanced results. Answer: Yes
* Yes - Poor-quality or incomplete training data increases cost because it drives more iterations:
additional data cleaning, relabeling, re-training, and re-evaluation to reach acceptable performance. It can also increase operational costs after deployment if the model produces low-quality outputs that require human rework, escalations, or incident handling. In practice, data quality debt becomes model cost debt.
* Yes - Training data is the primary mechanism by which AI models learn statistical patterns and relationships. For generative models, the training corpus shapes language fluency, factual associations, style tendencies, and the kinds of content the model can produce. Without sufficient and appropriate training signals, outputs degrade.
* Yes - If the training dataset is not representative of the real-world population or business context, the model can systematically underperform for certain groups, topics, or edge cases. This can manifest as biased language, missing perspectives, and uneven accuracy, producing "unbalanced" results. That is why Responsible AI practice emphasizes representative data, evaluation across slices, and continuous monitoring.
NEW QUESTION # 96
Your company is deploying Microsoft 365 Copilot. The deployment must provide users with access to the Researcher agent to search across data in Microsoft SharePoint. You need to recommend a licensing plan for the solution. What should you recommend?
Answer: C
Explanation:
The requirement is explicit: users must have access to the Researcher agent in Microsoft 365 Copilot and use it to search across organizational content stored in SharePoint . Microsoft's licensing guidance for Researcher indicates that Researcher is available to Microsoft 365 business and enterprise users who have a Microsoft 365 Copilot add-on license (and also to certain consumer "Microsoft 365 Premium" subscriptions).
That maps directly to option C . The Researcher agent is part of the Microsoft 365 Copilot experience for work tenants; it is not enabled merely by having a baseline Microsoft 365 subscription entitlement (B).
Baseline subscriptions can provide access to Microsoft 365 apps and content repositories (like SharePoint
/OneDrive), but the Researcher agent itself is a Copilot capability that requires the Copilot add-on to unlock.
Option A (pay-as-you-go) and D (usage-based consumption license in Azure) describe consumption models that apply to Azure services or agent metering in some scenarios, but they are not the standard licensing requirement to enable the built-in Researcher agent for Microsoft 365 Copilot users. When the goal is to enable Researcher inside Microsoft 365 Copilot for staff, the practical and correct recommendation is to assign the Microsoft 365 Copilot per-user add-on license to the users who need it, ensuring their SharePoint access is already properly permissioned and governed.
NEW QUESTION # 97
HOTSPOT - 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:
The answer Area
* You can use Azure Language in Foundry Tools to analyze the sentiment of customer reviews. Answer:
Yes
* You can use Azure Language in Foundry Tools to translate internal reports into multiple languages.
The answer: No
* You can use Azure Language in Foundry Tools to extract text from scanned documents. Answer: No Azure Language is designed for natural language processing (NLP) over text that is already machine- readable. That includes capabilities like sentiment analysis , key phrase extraction, entity recognition, summarization, and classification. Therefore, statement 1 is Yes : sentiment analysis of customer reviews is a standard NLP workload where the service scores text as positive/negative/neutral (and often provides confidence scores), helping organizations quantify customer satisfaction and detect recurring issues.
Statement 2 is No because translation is typically handled by a dedicated translation capability (commonly delivered as a separate translator service) rather than the core "Language" NLP features. While translation is an AI language workload, it's not what the Azure Language service is primarily used for in this context; the expected Microsoft service choice for multi-language translation is the translator capability, not Azure Language.
Statement 3 is No because extracting text from scanned documents is OCR (optical character recognition), which is a computer vision/document processing function. OCR is delivered through Azure Vision and/or Azure Document Intelligence , which can read printed/handwritten text from images and PDFs and return structured output. Azure Language can analyze extracted text after OCR, but it does not perform the image-to- text extraction step itself.
NEW QUESTION # 98
Your company plans to adopt AI across multiple business units.
You need to ensure that all AI projects align with the company's business strategy and are implemented responsibly.
What is the best approach to achieve the goal? More than one answer choice may achieve the goal. Select the BEST answer.
Answer: B
NEW QUESTION # 99
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:
* A manufacturer can use Azure Vision in Foundry Tools to identify product defects on an assembly line.
The answer: Yes
* A logistics company can use Azure Vision in Foundry Tools to recognize package shipping labels.
The answer: Yes
* The HR department at your company can only use Azure Vision in Foundry Tools to extract written content from Microsoft Word files. Answer: No Azure Vision in Foundry Tools provides computer vision capabilities to analyze images, including identifying visual features and reading text with OCR. Because it is designed to "analyze images" and support vision scenarios, it can be applied to manufacturing quality inspection use cases where the goal is to detect anomalies/defects from images captured on a production line. This aligns with statement 1 being Yes .
Statement 2 is also Yes because recognizing shipping labels is fundamentally text extraction from images (often plus some layout/field parsing). Azure Vision supports optical character recognition (OCR) to read printed text from images, and Microsoft documentation explicitly notes OCR can extract text from images such as product labels and similar real-world text surfaces-making shipping labels a direct fit.
Statement 3 is No because it is incorrectly restrictive. Azure Vision is not limited to extracting written content from Word documents, nor is OCR restricted to Word files. Vision capabilities apply broadly to images (and, depending on the capability, various document/image inputs) for tasks like image analysis and text recognition. HR could use it for many scenarios such as extracting text from scanned images, photos, or other visual inputs-not "only" Word files.
NEW QUESTION # 100
......
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