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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identify the business value of generative AI solutions | 35–40% | - AI value identification
|
| Topic 2: Identify benefits, capabilities, and opportunities for Microsoft AI apps and services | 35–40% | - Microsoft AI ecosystem
|
| Topic 3: Identify an implementation and adoption strategy for Microsoft AI apps and services | 20–25% | - AI adoption strategy
|
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NEW QUESTION # 78
Your company plans to use an AI-powered solution to analyze customer feedback for insights related to future product designs. You need to mitigate the privacy risks associated with the solution. What is the best approach to achieve the goal? Select the BEST answer.
Answer: C
Explanation:
The strongest privacy risk mitigation for analyzing customer feedback is to minimize personal data exposure while preserving the analytical value of the text. A is best because anonymizing (or de-identifying) the dataset removes direct identifiers (names, emails, phone numbers, addresses, account IDs) and reduces the likelihood of privacy breaches, unauthorized re-identification, or inadvertent leakage in model outputs. This aligns with privacy-by-design and the general principle of data minimization: only retain the information necessary for the business purpose.
B is usually impractical and undermines business value and auditability; organizations often need retention windows for validation, traceability, and improvement. C is not the best privacy mitigation: keeping data attributable to individuals increases privacy exposure; while deletion-on-request is important for compliance, it's not the primary mechanism to reduce privacy risk during analysis. D is explicitly poor practice; privacy reviews should occur throughout the lifecycle (requirements, design, data acquisition, testing, deployment, monitoring), not only at the end. Therefore, anonymizing/removing PII at the source is the best first-line approach.
NEW QUESTION # 79
Select the answer that correctly completes the sentence.
When a generative AI model produces output that seems realistic but contains incorrect information, the behavior is known as __________.
Answer:
Explanation:
Explanation:
model inaccuracy
The scenario describes a model producing plausible-sounding content that is factually wrong -a common generative AI failure mode often referred to as a "hallucination." Since "hallucination" is not offered in the dropdown, the best matching choice is model inaccuracy because the core problem is that the model's output is incorrect even though it appears confident and coherent.
The other options do not fit the definition of the behavior: data leakage is about sensitive information being exposed (for example, proprietary prompts, secrets, or personal data). Prompt injection is an attack technique where a user tries to override system instructions or cause unsafe actions. Overreliance describes a human
/organizational risk -trusting the model too much-rather than the model's intrinsic behavior of generating incorrect facts. Overreliance can be a consequence of this behavior, but it is not what the behavior itself is called.
In practice, you mitigate this kind of inaccuracy by grounding responses in trusted sources (for example, RAG), constraining prompts with explicit requirements, using verification steps (citations, cross-checking, tool-based validation), and adding human review for high-impact use cases.
NEW QUESTION # 80
Hotspot Question
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:
NEW QUESTION # 81
HOTSPOT - Select the answer that correctly completes the sentence.
You use __________ to train a model that will forecast product demand based on historical sales data.
Answer:
Explanation:
Explanation:
Azure Machine Learning
Forecasting product demand from historical sales data is a predictive analytics / machine learning use case. It typically requires selecting an appropriate forecasting approach (for example, regression, tree-based methods, or time-series models), preparing and splitting historical data, training and validating the model, tuning hyperparameters, and then deploying the model for ongoing inference. The Microsoft service designed to support that end-to-end ML lifecycle is Azure Machine Learning, which is why it correctly completes the sentence.
Azure Machine Learning provides the tooling and infrastructure to: manage datasets, run training jobs on scalable compute, track experiments, compare model performance, register models, and operationalize them through managed endpoints and pipelines. This makes it well-suited for iterative forecasting work, where you may retrain on new data regularly, monitor drift, and update models as product lines, promotions, or seasonality patterns change.
The other options do not directly fit "train a model" for forecasting. Azure AI Search is an indexing/retrieval service used to search and ground generative AI responses, not for training predictive models. Azure OpenAI provides access to large language and multimodal models for generative tasks (drafting, summarizing, Q & A) and is not the primary platform for building classical forecasting models. Microsoft Foundry is a broader platform experience for building and governing AI apps and agents, but the specific service for training a forecasting model on historical sales data is Azure Machine Learning.
NEW QUESTION # 82
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Box: create a Microsoft Word document
Microsoft 365 Copilot can be used to _______________.
Microsoft 365 Copilot can be used to create, draft, and refine Microsoft Word documents through several methods:
Draft from Scratch: You can start a new blank document and use the Draft with Copilot box (accessible via the Copilot icon or Alt + I) to enter a natural language prompt, such as "Write a sales proposal for a new product".
Reference Existing Files: You can ask Copilot to draft a new document based on up to three existing files (like a PowerPoint or another Word doc) by using the Reference a file button or typing / followed by the filename in the prompt box.
Chat-to-Document: Using the Copilot Agent in Word, you can start a project in a chat interface to ideate and then seamlessly transition that content into a structured Word document.
Template Creation: Within the Microsoft 365 Copilot app, you can select "Create" to start a document from a pre-defined template.
Reference:
https://support.microsoft.com/en-us/office/welcome-to-copilot-in-word-2135e85f-a467-463b-b2f0- c51a46d625d1
NEW QUESTION # 83
......
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