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| Section | Weight | Objectives |
|---|---|---|
| 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 an implementation and adoption strategy for Microsoft's AI apps and services | 20-25% | - Align an AI strategy with Microsoft responsible AI policies
|
| Identify the business value of generative AI solutions | 35-40% | - Identify the foundational concepts of generative AI
|
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NEW QUESTION # 42
- What should you use for each task? To answer, select the appropriate options in the answer area. NOTE:
Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Answer Area
* Extracting structured data from forms and invoices: Answer: Azure Document Intelligence in Foundry Tools
* Summarizing written content from business reports: Answer: Azure Language in Foundry Tools
* Generating descriptive text for uploaded images: Answer: Azure Vision in Foundry Tools These three tasks align to three different Azure AI capability families: document processing, language understanding/generation, and computer vision.
* Forms and invoices are semi-structured documents where the business need is to extract specific fields (IDs, names, totals, dates) reliably into structured output. Azure Document Intelligence is designed for intelligent document processing and includes prebuilt models (such as invoices) as well as custom extraction options, making it the correct choice for structured data extraction from documents.
* Summarizing written business reports is an NLP task focused on compressing long text into key points, themes, and action items. Azure Language provides language processing capabilities (including summarization features within language service capabilities), so it is the best fit for summarization scenarios.
* Generating descriptive text for images (image captioning/description) is a computer vision task.
Azure Vision can analyze uploaded images and return descriptions/captions and other visual insights, which directly matches the requirement to produce descriptive text from images.
NEW QUESTION # 43
An organization is adopting generative AI solutions and wants to ensure systems are designed to minimize bias, protect user data, and operate transparently.
Which Microsoft Responsible AI principle best aligns with this strategy?
Answer: D
Explanation:
Fairness is correct because the fairness principle in Microsoft Responsible AI focuses on ensuring AI systems treat individuals and groups equitably, minimizing harmful bias and discriminatory outcomes. This includes evaluating training data, model behavior, and generated outputs to prevent unequal treatment. While the scenario also references transparency and data protection, minimizing bias is most directly aligned with the fairness principle.
References:
https://learn.microsoft.com/en-us/training/modules/embrace-responsible-ai-principles-practices/1- introduction
https://learn.microsoft.com/en-us/azure/ai-foundry/responsible-use-of-ai-overview?view=foundry- classic
NEW QUESTION # 44
Your company plans to use generative AI to help build a website that will showcase various existing products. Which capability best describes a benefit of using generative AI for this project?
More than one answer choice may achieve the goal. Select the BEST answer.
Answer: B
Explanation:
Generative AI (GenAI) can significantly streamline the creation and localization of a product showcase website. Beyond standard word-for-word translation, GenAI tools--particularly those powered by Large Language Models (LLMs)--provide context-aware localization that adapts product descriptions to specific cultural nuances and brand tones.
Key Benefits of GenAI for Product Descriptions
Context-Aware Translation: Unlike older machine translation, GenAI understands the "intent" behind phrases, correctly handling idioms and technical terminology relevant to the product category.
Tone & Style Adaptation: You can instruct AI to translate a description into a "professional,"
"creative," or "technical" tone depending on the target audience.
Scalability: GenAI can process thousands of product listings simultaneously, reducing time-to- market by up to 90% compared to manual translation.
SEO Optimization: Some tools can automatically incorporate localized keywords into the translated description to improve search visibility in different regions.
Reference:
https://amplience.com/blog/create-personalized-product-descriptions-that-convert-with-ai
NEW QUESTION # 45
- What should you use for each task? To answer, select the appropriate options in the answer area. NOTE:
Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Answer Area
* Extracting structured data from forms and invoices: Answer: Azure Document Intelligence in Foundry Tools
* Summarizing written content from business reports: Answer: Azure Language in Foundry Tools
* Generating descriptive text for uploaded images: Answer: Azure Vision in Foundry Tools These three tasks align to three different Azure AI capability families: document processing, language understanding/generation, and computer vision.
* Forms and invoices are semi-structured documents where the business need is to extract specific fields (IDs, names, totals, dates) reliably into structured output. Azure Document Intelligence is designed for intelligent document processing and includes prebuilt models (such as invoices) as well as custom extraction options, making it the correct choice for structured data extraction from documents.
* Summarizing written business reports is an NLP task focused on compressing long text into key points, themes, and action items. Azure Language provides language processing capabilities (including summarization features within language service capabilities), so it is the best fit for summarization scenarios.
* Generating descriptive text for images (image captioning/description) is a computer vision task.
Azure Vision can analyze uploaded images and return descriptions/captions and other visual insights, which directly matches the requirement to produce descriptive text from images.
NEW QUESTION # 46
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
* Allowing AI models to make autonomous decisions supports the Microsoft responsible AI principle of accountability. Answer: No
* Regularly testing AI models for fairness and inclusiveness helps ensure they align with Microsoft's Responsible AI principles. Answer: Yes
* Protecting user data and limiting access to personal information supports the Microsoft responsible AI principles of privacy and security. Answer: Yes Microsoft's Responsible AI principles emphasize that people and organizations must remain accountable for AI systems and their outcomes. Accountability is strengthened by governance, human oversight, clear ownership, auditability, and processes to review and address issues-not by letting models make unchecked autonomous decisions. Therefore, statement 1 is No : increasing autonomy can actually increase risk unless paired with human-in-the-loop controls and clear escalation paths, because accountability requires clear responsibility for decisions and impacts.
Statement 2 is Yes because fairness and inclusiveness are explicitly supported through ongoing evaluation.
Regular testing helps detect disparate impact, performance gaps across user groups, and unintended bias introduced by data drift or changes in usage patterns. It's not a one-time activity; it's continuous assurance that the system behaves appropriately as conditions change.
Statement 3 is Yes because privacy and security are directly supported by protecting personal/sensitive data, enforcing least privilege access, and implementing controls such as data loss prevention, encryption, access logging, and strong identity governance. Limiting access to personal information reduces exposure and supports compliance obligations while aligning with privacy-by-design and secure-by-design expectations for AI-enabled solutions.
NEW QUESTION # 47
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