ExamGecko
Home Home / Microsoft / AI-102

Microsoft AI-102 Practice Test - Questions Answers, Page 3

Question list
Search
Search

List of questions

Search

Related questions











DRAG DROP

You are using a Language Understanding service to handle natural language input from the users of a web-based customer agent.

The users report that the agent frequently responds with the following generic response: "Sorry, I don't understand that." You need to improve the ability of the agent to respond to requests.

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. (Choose three.)

Question 21
Correct answer: Question 21

Explanation:

Step 1: Add prebuilt domain models as required.

Prebuilt models provide domains, intents, utterances, and entities. You can start your app with a prebuilt model or add a relevant model to your app later. Note: Language Understanding (LUIS) provides prebuilt domains, which are pre-trained models of intents and entities that work together for domains or common categories of client applications.

The prebuilt domains are trained and ready to add to your LUIS app. The intents and entities of a prebuilt domain are fully customizable once you've added them to your app.

Step 2: Enable active learning

To enable active learning, you must log user queries. This is accomplished by calling the endpoint query with the log=true querystring parameter and value.

Step 3: Train and republish the Language Understanding model

The process of reviewing endpoint utterances for correct predictions is called Active learning. Active learning captures endpoint queries and selects user's endpoint utterances that it is unsure of. You review these utterances to select the intent and mark entities for these real-world utterances. Accept these changes into your example utterances then train and publish. LUIS then identifies utterances more accurately.

Incorrect Answers:

Enable log collection by using Log Analytics

Application authors can choose to enable logging on the utterances that are sent to a published application. This is not done through Log Analytics.

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-review-endpoint-utterances#log-user-queries-to-enable-active-learning

https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-prebuilt-model

HOTSPOT

You are building a chatbot by using the Microsoft Bot Framework Composer.

You have the dialog design shown in the following exhibit.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Question 22
Correct answer: Question 22

Explanation:

Box 1: No

User.name is a property.

Box 2: Yes

Box 3: Yes

The coalesce() function evaluates a list of expressions and returns the first non-null (or non-empty for string) expression.

Reference:

https://docs.microsoft.com/en-us/composer/concept-language-generation

https://docs.microsoft.com/en-us/azure/data-explorer/kusto/query/coalescefunction

HOTSPOT

You are building a chatbot for a Microsoft Teams channel by using the Microsoft Bot Framework SDK. The chatbot will use the following code.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Question 23
Correct answer: Question 23

Explanation:

Box 1: Yes

The ActivityHandler.OnMembersAddedAsync method overrides this in a derived class to provide logic for when members other than the bot join the conversation, such as your bot's welcome logic.

Box 2: Yes

membersAdded is a list of all the members added to the conversation, as described by the conversation update activity. Box 3: No

Reference:

https://docs.microsoft.com/en-us/dotnet/api/microsoft.bot.builder.activityhandler.onmembersaddedasync?view=botbuilder-dotnet-stable

HOTSPOT

You are reviewing the design of a chatbot. The chatbot includes a language generation file that contains the following fragment.

# Greet(user)

- ${Greeting()}, ${user.name}

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Question 24
Correct answer: Question 24

Explanation:

Box 1: No

Example: Greet a user whose name is stored in `user.name`

- ${ welcomeUser(user.name) }

Example: Greet a user whose name you don't know:

- ${ welcomeUser() }

Box 2: No

Greet(User) is a Send a response action.

Box 3: Yes

Reference:

https://docs.microsoft.com/en-us/composer/how-to-ask-for-user-input

HOTSPOT

You are building a chatbot by using the Microsoft Bot Framework SDK.

You use an object named UserProfile to store user profile information and an object named ConversationData to store information related to a conversation.

You create the following state accessors to store both objects in state.

var userStateAccessors = _userState.CreateProperty<UserProfile>(nameof(UserProfile));

var conversationStateAccessors = _conversationState.CreateProperty<ConversationData>(nameof(ConversationData));

The state storage mechanism is set to Memory Storage.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Question 25
Correct answer: Question 25

Explanation:

Box 1: Yes

You create property accessors using the CreateProperty method that provides a handle to the BotState object. Each state property accessor allows you to get or set the value of the associated state property.

Box 2: Yes

Box 3: No

Before you exit the turn handler, you use the state management objects' SaveChangesAsync() method to write all state changes back to storage.

Reference:

https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-howto-v4-state

HOTSPOT

You are building a chatbot that will provide information to users as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.

NOTE: Each correct selection is worth one point.

Question 26
Correct answer: Question 26

Explanation:

Box 1: A Thumbnail card

A Thumbnail card typically contains a single thumbnail image, some short text, and one or more buttons.

Incorrect Answers:

an Adaptive card is highly customizable card that can contain any combination of text, speech, images, buttons, and input fields.

a Hero card typically contains a single large image, one or more buttons, and a small amount of text.

Box 2: an image

Reference:

https://docs.microsoft.com/en-us/microsoftteams/platform/task-modules-and-cards/cards/cards-reference

HOTSPOT

You are building a bot and that will use Language Understanding.

You have a LUDown file that contains the following content.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.

NOTE: Each correct selection is worth one point.

Question 27
Correct answer: Question 27

Explanation:

Reference:

https://github.com/solliancenet/tech-immersion-data-ai/blob/master/ai-exp1/README.md

HOTSPOT

You are designing a conversation flow to be used in a chatbot.

You need to test the conversation flow by using the Microsoft Bot Framework Emulator.

How should you complete the .chat file? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Question 28
Correct answer: Question 28

Explanation:

Reference:

https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-howto-add-media-attachments?view=azure-bot-service-4.0&tabs=csharp

You are building a chatbot by using the Microsoft Bot Framework Composer as shown in the exhibit. (Click the Exhibit tab.)

The chatbot contains a dialog named GetUserDetails. GetUserDetails contains a TextInput control that prompts users for their name.

The user input will be stored in a property named name.

You need to ensure that you can dispose of the property when the last active dialog ends.

Which scope should you assign to name?

A.
dialog
A.
dialog
Answers
B.
user
B.
user
Answers
C.
turn
C.
turn
Answers
D.
conversation
D.
conversation
Answers
Suggested answer: A

Explanation:

The dialog scope associates properties with the active dialog. Properties in the dialog scope are retained until the dialog ends.

Incorrect Answers:

A: The conversation scope associates properties with the current conversation. Properties in the conversation scope have a lifetime of the conversation itself. These properties are in scope while the bot is processing an activity associated with the conversation (for example, multiple users together in a Microsoft Teams channel).

B: The user scope associates properties with the current user. Properties in the user scope do not expire. These properties are in scope while the bot is processing an activity associated with the user.

C: The turn scope associates properties with the current turn. Properties in the turn scope expire at the end of the turn.

Reference:

https://docs.microsoft.com/en-us/composer/concept-memory?tabs=v2x

DRAG DROP

You have a chatbot that uses a QnA Maker application.

You enable active learning for the knowledge base used by the QnA Maker application.

You need to integrate user input into the model.

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.

Question 30
Correct answer: Question 30

Explanation:

Step 1: For the knowledge base, select Show active learning suggestions.

In order to see the suggested questions, on the Edit knowledge base page, select View Options, then select Show active learning suggestions.

Step 2: Approve and reject suggestions.

Each QnA pair suggests the new question alternatives with a check mark, ?, to accept the question or an x to reject the suggestions. Select the check mark to add the question.

Step 3: Save and train the knowledge base.

Select Save and Train to save the changes to the knowledge base.

Step 4: Publish the knowledge base.

Select Publish to allow the changes to be available from the GenerateAnswer API.

When 5 or more similar queries are clustered, every 30 minutes, QnA Maker suggests the alternate questions for you to accept or reject.

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/improve-knowledge-base

Total 309 questions
Go to page: of 31