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Microsoft AB-410 Exam Syllabus Topics:

Section	Weight	Objectives
Build intelligent apps with Copilot and agents	30%	- Integrate Copilot into canvas and model-driven apps 1. Customize Copilot responses and behavior 2. Configure Copilot features and prompts - Create and manage agents with Copilot Studio 1. Design agent logic and conversation flows 2. Connect agents to data and services
Create a foundation for intelligent applications	28%	- Implement responsible AI principles 1. Ensure transparency and fairness 2. Apply governance and compliance rules - Design solutions using AI-enabled tools 1. Recommend environment and ALM strategies 2. Evaluate built-in agents and AI capabilities 3. Analyze requirements and select components
Extend and secure intelligent solutions	20%	- Deploy, monitor, and maintain solutions 1. Manage solution lifecycle 2. Monitor performance and usage - Secure access and data 1. Configure roles and permissions 2. Apply data protection policies
Enhance solutions with AI and automation	22%	- Use AI Hub models and pre-built capabilities 1. Integrate generative AI features 2. Implement text, image, and document processing - Build automation with Power Automate 1. Add AI actions and triggers 2. Design flows using natural language

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Microsoft Building Intelligent Applications Sample Questions (Q100-Q105):

NEW QUESTION # 100
A company develops an AI chatbot using Azure OpenAI. Security administrators require that customer data must not be used to train public foundation models. Which statement correctly describes Azure OpenAI data handling?

A. Fine-tuning data becomes publicly searchable
B. All prompts are shared with external users
C. Customer prompts automatically train OpenAI public models
D. Customer data remains isolated from public model training

Answer: D

Explanation:
Azure OpenAI provides enterprise data protection where customer prompts, completions, and training data are not used to train public OpenAI models. Data isolation and security controls are key enterprise features. Organizations can build applications while maintaining control over their information. Public model improvement processes are separate from Azure OpenAI customer workloads.

NEW QUESTION # 101
You are building a canvas app for users to submit incident reports from their mobile devices.
When a user submits an incident form, the app must run a Power Automate cloud flow that sends a notification email.
You need to configure the canvas app to trigger the cloud flow after the user selects the Submit button.
What should you do?

A. Use the OnSelect property of the Submit button to call the flow by using the `Run()` function.
B. Use the OnSuccess property of the form control to call the flow by using `Launch()` and pass the necessary parameters.
C. Use the OnVisible property of the screen to call the flow by using the `Run()` function.
D. Use the OnSelect property of the Submit button to call the flow by using the `SubmitForm()` function.

Answer: A

Explanation:
Microsoft Power Apps canvas applications can invoke Power Automate cloud flows directly through Power Fx formulas. To trigger a flow when a user selects a button, the developer must associate the flow with the application and call its Run() function from the button ' s OnSelect property. The cloud flow should use the Power Apps trigger so that it can receive parameters passed from the application. These parameters might include an incident identifier, description, priority, or assigned recipient. The flow can then execute the required notification email action. SubmitForm() submits data through an Edit Form control but does not independently invoke a cloud flow. OnVisible executes when a screen becomes visible, making it unsuitable for an explicitly requested button action. Launch() opens a URL or application resource rather than invoking a connected flow directly.

NEW QUESTION # 102
A company develops an AI solution that extracts information from images, understands text, and generates responses. The architecture should combine multiple AI capabilities through managed services. Which design approach is recommended?

A. Compose multiple specialized AI services
B. Avoid using APIs
C. Build one unmanaged model only
D. Store all data inside prompts permanently

Answer: A

Explanation:
Modern intelligent applications commonly combine specialized AI services rather than relying on a single capability. For example, vision services can process images, language services can analyze text, and generative models can create responses. Composable architectures improve scalability, maintainability, and flexibility while allowing each service to handle its optimized workload.

NEW QUESTION # 103
A company uses a model-driven app to enforce data quality standards.
The company requires the following app functionality:
- Ensure users enter a value in a specific column when a condition is
met.
- Prevent users from saving the record until they complete the field.
- The solution must be implemented without using code or automation.
You need to configure a business rule to meet the requirements.
What should you do?

A. Set field visibility.
B. Set the requirement level.
C. Set a default value.
D. Show a recommendation.

Answer: B

Explanation:
You can satisfy all three requirements using a no-code Business Rule by setting the requirement level to Business Required.
This ensures that once your specific condition evaluates to true, the column becomes mandatory, a red asterisk appears, and the system dynamically prevents the user from saving the record until the field is populated.
Reference:
https://learn.microsoft.com/en-us/power-apps/maker/model-driven-apps/guide-staff-through-common-tasks-processes

NEW QUESTION # 104
You need to configure a Power Automate flow to send the email with the results to the client. What should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Trigger: Set Table name to Qualification and select/filter on the Status Reason column. Completion logic: List the related Qualification rows and complete the Service Request only if all are in Complete status.

The flow should start when a Qualification row is modified because completion of an individual qualification is the event that can make its parent Service Request eligible for completion. Configure the Dataverse trigger for the Qualification table and include the Status Reason column in Select columns so unrelated updates do not start the flow. Where appropriate, add an OData filter condition for the Complete status value. Triggering on Service Request would be too late because that row must be completed by the automation. The flow must then retrieve all Qualification rows related to the same Service Request and verify that every row has reached Complete. It must not decide from the current Qualification alone: one completed child does not prove that the other related qualifications are finished. If no incomplete child rows remain, the flow updates the parent status and sends the templated client email. Microsoft documents that Select columns limits Dataverse update triggers to requests containing designated scalar columns and that List rows supports OData filtering of related records.
Reference: https://learn.microsoft.com/en-us/power-automate/dataverse/create-update-delete-trigger Study Guide alignment: Build business application logic and automation.

NEW QUESTION # 105
......

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