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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Extend and secure intelligent solutions | 20% | - Secure access and data
|
| Topic 2: Create a foundation for intelligent applications | 28% | - Implement responsible AI principles
|
| Topic 3: Enhance solutions with AI and automation | 22% | - Build automation with Power Automate
|
| Topic 4: Build intelligent apps with Copilot and agents | 30% | - Create and manage agents with Copilot Studio
|
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NEW QUESTION # 104
A developer builds a chatbot that must remember previous messages during a user session.
Which component is responsible for maintaining conversational context?
Answer: C
Explanation:
Conversation state management stores relevant previous interactions and provides context for future responses. Large language models do not automatically maintain memory between requests unless context is supplied. Image models, compression systems, and firewalls serve unrelated purposes. Proper state handling is essential for creating natural multi-turn conversational experiences.
NEW QUESTION # 105
Drag and Drop Question
A company uses a cloud flow to process customer records in Dataverse.
The flow must:
- Retrieve a customer record.
- Store the customer email address for later use.
- Use the stored value in an email action.
You need to configure flow actions.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Answer:
Explanation:
Explanation:
Step 1: Get a row by ID (Dataverse)
Retrieve the specific customer record.
Step 2: Initialize a variable
Create a string variable to hold the email address.
Step 3: Set variable
Store the customer's email address in the initialized variable
Step 4: Send an email
Pass the stored email variable into the "To" field of the email action
Reference:
https://learn.microsoft.com/en-us/power-automate/create-variable-store-values
NEW QUESTION # 106
An organization deploys an AI application handling customer information. The company must ensure transparency regarding AI-generated decisions and provide explanations to users. Which responsible AI principle applies?
Answer: D
Explanation:
Transparency is a responsible AI principle focused on explaining how AI systems operate and how decisions are produced. Users should understand when AI is involved and receive appropriate information about outcomes. Hardware optimization and compression improve technical performance but do not address ethical requirements or user understanding.
NEW QUESTION # 107
You need to implement a generative AI solution that meets the requirements.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: B,D
Explanation:
The solution should use a prebuilt AI capability where it satisfies the complaint-processing requirement and create the generative prompt from blank for the organization-specific inspection report. Using a prebuilt model minimizes custom model development and training effort, which directly reflects the stated constraint.
A blank custom prompt gives the maker control over the inspection template, instructions, inputs, tone, and output format required by the business. Starting from a prompt template can accelerate common scenarios, but the case requires alignment to an existing custom inspection format; a blank prompt avoids carrying irrelevant template assumptions and permits deliberate grounding. Building a custom trained model would add data preparation, training, validation, and lifecycle overhead that the requirement seeks to minimize. The prompt should define required inputs explicitly and be tested with representative data to prevent the inconsistent output problem identified in the case. The Study Guide covers "build prompts from templates or from blank,"
"add inputs to a prompt," and consumption of AI capabilities in apps and flows. Options A and C provide the lowest-custom-development design that still supports the specific generative output.
Study Guide reference/topic: "Create prompts and models in AI Hub - Build prompts and consume AI capabilities." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 108
A company is using Microsoft Dataverse.
You must integrate Dataverse with a third-party AI service. The solution requires authentication and custom request handling to send and receive data.
You need to enable the integration.
What should you do?
Answer: D
Explanation:
A custom connector is required to integrate with the third-party AI service because the integration needs a defined authentication scheme and custom request handling. The connector wraps the service's API as named operations, with host information, paths, methods, headers, parameters, request bodies, and response schemas.
Power Automate or Power Apps can then call those operations through governed connections instead of reconstructing raw requests in every solution. Power Fx is an expression language and does not by itself define or secure an external API contract. Microsoft 365 Copilot chat is a user productivity experience, not a Dataverse integration mechanism. An environment variable can store deployment-specific configuration such as a base URL or identifier, but it neither authenticates nor sends the API request. The connector should be packaged in a solution, use the service's supported API key or OAuth design, and comply with data loss prevention policies. This directly aligns with the Study Guide cloud-flow objective "evaluate and recommend connectors" and Microsoft's custom connector architecture.
Study Guide reference/topic: "Create cloud flows - Evaluate and recommend connectors." AB-410 Study Guide | Microsoft Learn technical reference
NEW QUESTION # 109
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