AI-102 無料問題集「Microsoft Designing and Implementing a Microsoft Azure AI Solution」
You are developing an internet-based training solution for remote learners.
Your company identifies that during the training, some learners leave their desk for long periods or become distracted.
You need to use a video and audio feed from each learner's computer to detect whether the learner is present and paying attention. The solution must minimize development effort and identify each learner.
Which Azure Cognitive Services service should you use for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Your company identifies that during the training, some learners leave their desk for long periods or become distracted.
You need to use a video and audio feed from each learner's computer to detect whether the learner is present and paying attention. The solution must minimize development effort and identify each learner.
Which Azure Cognitive Services service should you use for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
Scenario Recap
You are building a remote training monitoring solution.
Requirement: Use video and audio feeds to detect if a learner is present, paying attention, and talking.
Services available: Face, Speech, Text Analytics.
Analysis
From a learner's video feed, verify whether the learner is present.
The Face API can detect and identify faces in a video feed.
It can tell if a person is present and recognized, fulfilling the requirement.
From a learner's facial expression in the video feed, verify whether the learner is paying attention.
Again, the Face API provides facial expression and emotion recognition (happiness, anger, neutral, etc.).
This can be mapped to "paying attention vs. distracted."
From a learner's audio feed, detect whether the learner is talking.
The Speech service detects spoken input and can determine if speech is present.
Text Analytics works on text (not raw audio) and is therefore not appropriate here.
Final Answer (Answer Area Selections)
From a learner's video feed, verify whether the learner is present: Face From a learner's facial expression in the video feed, verify whether the learner is paying attention: Face From a learner's audio feed, detect whether the learner is talking: Speech Microsoft References Face API - Face detection & identification Face API - Emotion recognition Azure Speech service
You build a bot by using the Microsoft Bot Framework SDK.
You need to test the bot interactively on a local machine.
Which three 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.
You need to test the bot interactively on a local machine.
Which three 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.
正解：
Explanation:
Comprehensive Detailed Explanation
The question asks about testing a bot interactively on a local machine when using the Microsoft Bot Framework SDK.
Steps to test locally:
Build and run the bot
Compile the bot application code and run it locally (e.g., using Visual Studio or Node.js).
This exposes the bot's endpoint on localhost (commonly http://localhost:3978/api/messages ).
Open the Bot Framework Emulator
The Bot Framework Emulator is a desktop app for testing and debugging bots built with the Bot Framework SDK.
It allows you to send messages to the bot and see the responses.
Connect to the bot endpoint
Use the Emulator to connect to the locally running bot by entering its endpoint URL.
Once connected, you can interact with the bot as if you were a real user.
Actions Not Required in This Case
Register the bot with the Azure Bot Service # Needed for cloud deployment, not local testing.
Open the Bot Framework Composer # Only needed if designing the bot with Composer, but this scenario uses the SDK directly.
Correct Sequences (multiple possible valid orders):
Build and run the bot # Open the Bot Framework Emulator # Connect to the bot endpoint Microsoft References Test a bot locally with Bot Framework Emulator Bot Framework SDK overview
# Final Answer Sequence:
Build and run the bot
Open the Bot Framework Emulator
Connect to the bot endpoint
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
Normalization involves eliminating relationships between database tables.
No
Normalization does not eliminate relationships. In fact, it often creates relationships between tables by splitting data into smaller, related tables.
Normalizing a database reduces data redundancy.
Yes
The primary goal of normalization is to minimize duplicate data and ensure that each fact is stored only once.
Normalization improves data integrity.
Yes
By reducing redundancy and ensuring data is stored in a structured manner, normalization enforces consistency and integrity across the database.
Correct Responses:
No
Yes
Yes
Microsoft References
Database normalization basics
Database design and normalization
You have a web app that uses Azure AI search.
When reviewing activity, you see greater than expected search query volumes. You suspect that the query key is compromised.
You need to prevent unauthorized access to the search endpoint and ensure that users only have read only access to the documents collection. The solution must minimize app downtime.
Which three action should you perform in sequence? To answer, more the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
When reviewing activity, you see greater than expected search query volumes. You suspect that the query key is compromised.
You need to prevent unauthorized access to the search endpoint and ensure that users only have read only access to the documents collection. The solution must minimize app downtime.
Which three action should you perform in sequence? To answer, more the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
正解：
Explanation:
Comprehensive Detailed Explanation
You are dealing with Azure AI Search (formerly Azure Cognitive Search). The issue is that the query key is compromised, and you need to ensure minimal downtime while keeping users with read-only access.
Azure AI Search uses two types of keys:
Admin keys (full control - manage indexes, data sources, etc.)
Query keys (read-only access for client applications)
If a query key is compromised, the remediation must be safe and fast, without breaking the application unnecessarily.
Step 1 - Add a new query key
Instead of immediately deleting the compromised key, first generate a new query key in the Azure portal or via API. This ensures you have a replacement ready before cutting off the old key.
Step 2 - Change the app to use the new key
Update your web app configuration (for example, connection strings or environment variables) so that it authenticates against Azure AI Search using the newly created query key. This step ensures a smooth transition with minimal downtime.
Step 3 - Delete the compromised key
Finally, once your app is verified to work with the new query key, remove the old compromised key to prevent any further unauthorized access.
Correct Order:
Add a new query key.
Change the app to use the new key.
Delete the compromised key.
Microsoft References
Manage admin and query keys in Azure AI Search
Best practices for key management
You have a chatbot that was built by using the Microsoft Bot Framework. You need to debug the chatbot endpoint remotely.
Which two tools should you install on a local computer? Each correct answer presents part of the solution.
(Choose two.)
NOTE: Each correct selection is worth one point.
Which two tools should you install on a local computer? Each correct answer presents part of the solution.
(Choose two.)
NOTE: Each correct selection is worth one point.
正解：A、E
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解説: (JPNTest メンバーにのみ表示されます)
You ace building an internet-based training solution. The solution requires that a user ' s camera and microphone remain enabled.
You need to monitor a video stream ol the user and detect when the user asks an instructor a question. The solution must minimize development effort.
What should you include in the solution?
You need to monitor a video stream ol the user and detect when the user asks an instructor a question. The solution must minimize development effort.
What should you include in the solution?
正解：C
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解説: (JPNTest メンバーにのみ表示されます)
You are designing two Azure Al agents named Agent 1 and Agent2 to assist different departments at your company. Each agent will have access to sensitive corporate data. The design must meet the following requirements:
* Agentl must process specific user queries and provide relevant answers in a conversational format
* Agent2 must perform the following actions:
o Adapt actions based on patterns in user behavior, o Understand and learn from historical data.
o Provide proactive recommendations.
Which type of agent should you recommend for each agent? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
* Agentl must process specific user queries and provide relevant answers in a conversational format
* Agent2 must perform the following actions:
o Adapt actions based on patterns in user behavior, o Understand and learn from historical data.
o Provide proactive recommendations.
Which type of agent should you recommend for each agent? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
You are building a Conversational Language Understanding model.
You need to ensure that the model will support the following sample utterances:
* Set all the lights to on.
* Turn off the lights in the living room.
* What is the current thermostat temperature?
* Lower the temperature of the thermostat by five degrees.
Which three elements should you add to the model?
Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
You need to ensure that the model will support the following sample utterances:
* Set all the lights to on.
* Turn off the lights in the living room.
* What is the current thermostat temperature?
* Lower the temperature of the thermostat by five degrees.
Which three elements should you add to the model?
Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
正解：B、C、D
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解説: (JPNTest メンバーにのみ表示されます)
You are building a Language Understanding model for purchasing tickets.
You have the following utterance for an intent named PurchaseAndSendTickets.
Purchase [2 audit business] tickets to [Paris] [next Monday] and send tickets to [[email protected]] You need to select the entity types. The solution must use built-in entity types to minimize training data whenever possible.
Which entity type should you use for each label? To answer, drag the appropriate entity types to the correct labels. Each entity type may be used once, more than once, or not at all.
You may need to drag the split bar between panes or scroll to view content.
You have the following utterance for an intent named PurchaseAndSendTickets.
Purchase [2 audit business] tickets to [Paris] [next Monday] and send tickets to [[email protected]] You need to select the entity types. The solution must use built-in entity types to minimize training data whenever possible.
Which entity type should you use for each label? To answer, drag the appropriate entity types to the correct labels. Each entity type may be used once, more than once, or not at all.
You may need to drag the split bar between panes or scroll to view content.
正解：
Explanation:
Box 1: GeographyV2
The prebuilt geographyV2 entity detects places. Because this entity is already trained, you do not need to add example utterances containing GeographyV2 to the application intents.
Box 2: Email
Email prebuilt entity for a LUIS app: Email extraction includes the entire email address from an utterance.
Because this entity is already trained, you do not need to add example utterances containing email to the application intents.
Box 3: Machine learned
The machine-learning entity is the preferred entity for building LUIS applications.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-geographyv2
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-email
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/reference-entity-machine-learned-entity
You need to create a new resource that will be used to perform sentiment analysis and optical character recognition (OCR). The solution must meet the following requirements:
Use a single key and endpoint to access multiple services.
Consolidate billing for future services that you might use.
Support the use of Computer Vision in the future.
How should you complete the HTTP request to create the new resource? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Use a single key and endpoint to access multiple services.
Consolidate billing for future services that you might use.
Support the use of Computer Vision in the future.
How should you complete the HTTP request to create the new resource? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
To create a single multi-service Cognitive Services resource (now Azure AI Services) that provides one key
/endpoint for multiple services , consolidates billing, and allows adding services like Text Analytics (sentiment analysis) and Computer Vision (OCR) from the same resource, you must:
Use the Azure Resource Manager (ARM) REST API with PUT to create or update the account:
PUT /subscriptions/{subId}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{name}?
api-version=2017-04-18
Set " kind " : " CognitiveServices " to create the multi-service account (not a single-service kind like ComputerVision or TextAnalytics).
This satisfies the requirements: single key/endpoint, consolidated billing, and future Computer Vision use.
Microsoft Azure AI Solution References
ARM REST for Cognitive Services accounts (create/update via PUT , multi-service " kind " : " CognitiveServices " ).
https://learn.microsoft.com/azure/ai-services/management/resource-manager-create-account Azure AI Services multi-service resource (single endpoint/key across services).
https://learn.microsoft.com/azure/ai-services/multi-service-resource
You are building a flight booking bot by using the Microsoft Bot Framework SDK.
The bot will ask users for their departure date. The bot must repeat the question until a valid date is given, or the users cancel the transaction.
Which type of dialog should you use?
The bot will ask users for their departure date. The bot must repeat the question until a valid date is given, or the users cancel the transaction.
Which type of dialog should you use?
正解：D
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解説: (JPNTest メンバーにのみ表示されます)
You have an Azure subscription.
You need to deploy an Azure Al Document Intelligence resource.
How should you complete the Azure Resource Manager (ARM) template? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to deploy an Azure Al Document Intelligence resource.
How should you complete the Azure Resource Manager (ARM) template? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
Explanation:
Azure AI Document Intelligence (formerly Form Recognizer) is provisioned as a Cognitive Services account with the kind set to FormRecognizer . In an ARM template, Document Intelligence is created under the resource provider Microsoft.CognitiveServices with the resource type accounts . Therefore:
type must be " Microsoft.CognitiveServices/accounts "
kind must be " FormRecognizer "
This aligns with Microsoft's ARM schema for Cognitive Services accounts and the documented way to deploy Document Intelligence.
Key references from Microsoft documentation:
Azure Resource Manager template reference for Cognitive Services accounts - shows type: Microsoft.
CognitiveServices/accounts and supported kind values including FormRecognizer .
https://learn.microsoft.com/azure/templates/microsoft.cognitiveservices/accounts Azure AI Document Intelligence (Form Recognizer) resource creation guidance - indicates the service is deployed as a Cognitive Services account with kind FormRecognizer .
https://learn.microsoft.com/azure/ai-services/document-intelligence/overview Create Document Intelligence resources (portal/ARM/Bicep) - reiterates Cognitive Services account with FormRecognizer kind.
https://learn.microsoft.com/azure/ai-services/document-intelligence/create-resources