microsoft ai-102 practice test
Designing and Implementing an Azure AI Solution
Note: Test Case questions are at the end of the exam
Question 1 Topic 6, Mixed Questions
You need to enable speech capabilities for a chatbot.
Which three actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. Enable WebSockets for the chatbot app.
- B. Create a Speech service.
- C. Register a Direct Line Speech channel.
- D. Register a Cortana channel.
- E. Enable CORS for the chatbot app.
- F. Create a Language Understanding service.
Answer:
A B C
Explanation:
You can use the Speech service to voice-enable a chat bot.
The Direct Line Speech channel uses the text-to-speech service, which has neural and standard voices.
You'll need to make a small configuration change so that your bot can communicate with the Direct Line Speech channel
using web sockets.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/tutorial-voice-enable-your-bot-speech-sdk
Question 2 Topic 6, Mixed Questions
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.
Select and Place:
Answer:
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.
, to accept the question or an x to reject the
Each QnA pair suggests the new question alternatives with a check mark,
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
Question 3 Topic 6, Mixed Questions
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
- B. user
- C. turn
- D. conversation
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
Question 4 Topic 6, Mixed Questions
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.
Hot Area:
Answer:
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
Question 5 Topic 6, Mixed Questions
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.
Hot Area:
Answer:
Explanation:
Reference: https://github.com/solliancenet/tech-immersion-data-ai/blob/master/ai-exp1/README.md
Question 6 Topic 6, Mixed Questions
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.
Hot Area:
Answer:
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
Implement Conversational AI Solutions
Question 7 Topic 6, Mixed Questions
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(nameof(UserProfile)); var conversationStateAccessors =
_conversationState.CreateProperty(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.
Hot Area:
Answer:
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
Question 8 Topic 6, Mixed Questions
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.
Hot Area:
Answer:
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
Question 9 Topic 6, Mixed Questions
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.
Hot Area:
Answer:
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
Question 10 Topic 6, Mixed Questions
You build a conversational bot named bot1.
You need to configure the bot to use a QnA Maker application.
From the Azure Portal, where can you find the information required by bot1 to connect to the QnA Maker application?
- A. Access control (IAM)
- B. Properties
- C. Keys and Endpoint
- D. Identity
Answer:
C
Explanation:
Obtain values to connect your bot to the knowledge base 1. In the QnA Maker site, select your knowledge base.
2. With your knowledge base open, select the SETTINGS tab. Record the value shown for service name. This value is useful
for finding your knowledge base of interest when using the QnA Maker portal interface. It's not used to connect your bot app
to this knowledge base.
3. Scroll down to find Deployment details and record the following values from the Postman sample HTTP request:
4. POST /knowledgebases//generateAnswer
5. Host:
6. Authorization: EndpointKey
Reference: https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-howto-qna
Question 11 Topic 6, Mixed 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.)
Select and Place:
Answer:
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
Question 12 Topic 6, Mixed Questions
You are building a bot on a local computer by using the Microsoft Bot Framework. The bot will use an existing Language
Understanding model.
You need to translate the Language Understanding model locally by using the Bot Framework CLI.
What should you do first?
- A. From the Language Understanding portal, clone the model.
- B. Export the model as an .lu file.
- C. Create a new Speech service.
- D. Create a new Language Understanding service.
Answer:
B
Explanation:
You might want to manage the translation and localization for the language understanding content for your bot
independently.
Translate command in the @microsoft/bf-lu library takes advantage of the Microsoft text translation API to automatically
machine translate .lu files to one or more than 60+ languages supported by the Microsoft text translation cognitive service.
What is translated?
An .lu file and optionally translate
Comments in the lu file
LU reference link texts
List of .lu files under a specific path.
Reference: https://github.com/microsoft/botframework-cli/blob/main/packages/luis/docs/translate-command.md
Question 13 Topic 6, Mixed Questions
DRAG DROP
You plan to build a chatbot to support task tracking.
You create a Language Understanding service named lu1.
You need to build a Language Understanding model to integrate into the chatbot. The solution must minimize development
time to build 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. (Choose four.)
Select and Place:
Answer:
Explanation:
Step 1: Add a new application
Create a new app
1. Sign in to the LUIS portal with the URL of https://www.luis.ai.
2. Select Create new app.
3. Etc.
Step 2: Add example utterances.
In order to classify an utterance, the intent needs examples of user utterances that should be classified with this intent.
Step 3: Train the application
Step 4: Publish the application
In order to receive a LUIS prediction in a chat bot or other client application, you need to publish the app to the prediction
endpoint.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/tutorial-intents-only
Question 14 Topic 6, Mixed Questions
You are building a multilingual chatbot.
You need to send a different answer for positive and negative messages.
Which two Text Analytics APIs should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. Linked entities from a well-known knowledge base
- B. Sentiment Analysis
- C. Key Phrases
- D. Detect Language
- E. Named Entity Recognition
Answer:
B D
Explanation:
B: The Text Analytics API's Sentiment Analysis feature provides two ways for detecting positive and negative sentiment. If
you send a Sentiment Analysis request, the API will return sentiment labels (such as "negative", "neutral" and "positive") and
confidence scores at the sentence and document-level.
D: The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and
returns language identifiers with a score that indicates the strength of the analysis.
This capability is useful for content stores that collect arbitrary text, where language is unknown.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-
analysis?tabs=version-3-1 https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-
how-to-language-detection
Question 15 Topic 6, Mixed Questions
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.
Hot Area:
Answer:
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