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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Create a foundation for intelligent applications | 28% | - Design solutions using AI-enabled tools
|
| Topic 2: Enhance solutions with AI and automation | 22% | - Use AI Hub models and pre-built capabilities
|
| Topic 3: Extend and secure intelligent solutions | 20% | - Deploy, monitor, and maintain solutions
|
| Topic 4: Build intelligent apps with Copilot and agents | 30% | - Create and manage agents with Copilot Studio
|
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NEW QUESTION # 21
A company is building a prompt about product specifications. The company plans to use the prompt in Power Automate.
The prompt must use Retrieval-Augmented Generation to ground the model with additional business information.
You need to select the available knowledge source for the prompt.
What should you use?
Answer: B
Explanation:
A Dataverse table is the best knowledge source for a Power Automate Retrieval-Augmented Generation (RAG) prompt handling product specifications.
Why Dataverse is better than PDF
Native Integration: Power Automate and Dataverse sit on the same Power Platform infrastructure.
This eliminates complex document parsing and connector lag.
Precise Grounding: AI models read structured rows and columns much more accurately than unstructured PDF layouts, tables, or multi-column text.
Real-Time Accuracy: Product specs change. Updating a Dataverse cell instantly updates the AI's knowledge. Modifying, re-uploading, and re-indexing a PDF creates version-control issues.
Accuracy: Minimizes model hallucinations because the AI reasons over discrete, low-code tabular data.
Reference:
https://microsoft.github.io/agent-academy/operative/08-dataverse-grounding/
NEW QUESTION # 22
A company builds a canvas app that processes images submitted by users and must classify them using an existing AI Builder model.
The app must generate predictions during user interaction.
You need to consume the AI model natively.
What should you do?
Answer: D
Explanation:
To process user-submitted images natively within a canvas app using an existing AI Builder model, you should Call the model from app logic.
By adding the AI model as a data source and calling its .Predict() method in your Power Fx formulas, the app evaluates the images dynamically while the user interacts with it.
Reference:
https://learn.microsoft.com/en-us/ai-builder/powerfx-in-powerapps
NEW QUESTION # 23
A company has a product report in PDF format. The report must be rewritten with formal vocabulary and cadence.
The company requires a prompt that can be used within a canvas app to rewrite the report as a Word document. The prompt must reference a business glossary stored in a SharePoint site.
You need to make a suggestion for the expectations portion of the prompt to generate a report summary correctly.
What should you suggest?
Answer: A
Explanation:
The best approach is "The summary should highlight key themes, product features, and recurring feedback." Choosing this approach is best because it provides explicit, actionable instructions to the AI model.
Incorrect:
[Not B]
Simply telling the AI to "use the PDF and the glossary" only identifies the sources of data; it does not explain what to do with that data or how to structure the output. Combining specific criteria (themes, features, feedback) with your source references ensures a high-quality, targeted summary.
Reference:
https://learn.microsoft.com/en-us/power-apps/maker/data-platform/prompt-column
NEW QUESTION # 24
A company builds a canvas app that processes images submitted by users and must classify them using an existing AI Builder model.
The app must generate predictions during user interaction.
You need to consume the AI model natively.
What should you do?
Answer: C
Explanation:
To natively consume an AI Builder model and generate predictions during user interaction using Power Fx, you must use the Predict function.
Reference:
https://learn.microsoft.com/en-us/ai-builder/use-in-powerapps-overview
NEW QUESTION # 25
A company processes customer orders by using a cloud flow.
The flow must evaluate the following conditions:
# Route orders for approval when the OrderTotal exceeds 1,000.
# Flag orders when the CustomerName identifies the string "VIP".
You need to configure flow conditions.
Which expressions should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
OrderTotal - greater(triggerOutputs()?['body/OrderTotal'], 1000); CustomerName - contains (triggerOutputs()?['body/CustomerName'] , 'VIP')
The approval condition must use greater(triggerOutputs()?['body/OrderTotal'], 1000) because the requirement is strictly "exceeds 1,000." equals would match only 1,000, and less would reverse the decision. The VIP test must use contains(triggerOutputs()?['body/CustomerName'] , 'VIP') because the requirement says the name identifies the string anywhere in the value. startsWith would miss names where VIP occurs later, and equals would match only a value consisting entirely of VIP. In production, the maker should confirm the trigger schema and ensure OrderTotal is numeric rather than text; conversion may be required when the source supplies a string. Case sensitivity and null handling should also be tested for customer names. These expressions can be used in Condition actions or trigger conditions depending on whether unwanted runs should be prevented entirely. The Study Guide explicitly includes "implement flow control with conditions and loops." The two selected functions translate the comparison language precisely: greater for the numeric threshold and contains for substring identification.
Study Guide reference/topic: "Create cloud flows - Implement flow control with conditions." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 26
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