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Question 1:

HOTSPOT

You plan to deploy a containerized version of an Azure Cognitive Services service that will be used for text analysis.

You configure https://contoso.cognitiveservices.azure.com as the endpoint URI for the service, and you pull the latest version of the Text Analytics Sentiment Analysis container.

You need to run the container on an Azure virtual machine by using Docker.

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

NOTE: Each correct selection is worth one point.

Hot Area:

Correct Answer:

Box 1: mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment

To run the Sentiment Analysis v3 container, execute the following docker run command.

docker run –rm -it -p 5000:5000 –memory 8g –cpus 1 \

mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment \

Eula=accept \

Billing={ENDPOINT_URI} \

ApiKey={API_KEY} is the endpoint for accessing the Text Analytics API. https://.cognitiveservices.azure.com

Box 2: https://contoso.cognitiveservices.azure.com

{ENDPOINT_URI} is the endpoint for accessing the Text Analytics API: https://.cognitiveservices.a The endpoint for accessing the Text Analytics API. zure.com

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-install-containers?tabs=sentiment

Question 2:

HOTSPOT

You develop an application that uses the Face API.

You need to add multiple images to a personal group.

How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Hot Area:

Correct Answer:

Box 1: Stream

The File.OpenRead(String) method opens an existing file for reading.

Example: Open the stream and read it back.

using (FileStream fs = File.OpenRead(path))

Box 2: AddFaceFromStreamAsync

Step 5 on https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-add-faces

Question 3:

HOTSPOT

You are developing an application that will use the Computer Vision client library. The application has 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:

Correct Answer:

Box 1: No

Box 2: Yes

The ComputerVision.analyzeImageInStreamAsync operation extracts a rich set of visual features based on the image content.

Box 3: Yes.

Reference:

https://docs.microsoft.com/en-us/java/api/com.microsoft.azure.cognitiveservices.vision.computervision.computervision.analyzeimageinstreamasync

Question 4:

HOTSPOT

You are developing a text-processing solution.

You develop the following method.

You call the method by using the following code.

GetKeyPhrases(textAnalyticsClient, “the cat sat on the mat”);

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:

Correct Answer:

Box 1: Yes

The Key Phrase Extraction API evaluates unstructured text, and for each JSON document, returns a list of key phrases.

Box 2: No

\’ the\’ is not a key phrase.

This capability is useful if you need to quickly identify the main points in a collection of documents. For example, given input text “The food was delicious and there was wonderful staff”, the service returns the main talking points: “food” and

“wonderful staff”.

Box 3: No

Key phrase extraction does not have confidence levels.

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-keyword-extraction

Question 5:

HOTSPOT

You are creating an enrichment pipeline that will use Azure Cognitive Search. The knowledge store contains unstructured JSON data and scanned PDF documents that contain text.

Which projection type should you use for each data type? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Hot Area:

Correct Answer:

Box 1: Object projection

Object projections are JSON representations of the enrichment tree that can be sourced from any node.

Box 2: File projection

File projections are similar to object projections and only act on the normalized_images collection.

Reference:

https://docs.microsoft.com/en-us/azure/search/knowledge-store-projection-overview

Question 6:

HOTSPOT

You are building an Azure Cognitive Search custom skill.

You have the following custom skill schema definition.

For each of the following statements, select Yes if the statement. Otherwise, select No. NOTE: Each correct selection is worth one point.

Hot Area:

Correct Answer:

Box 1: Yes

Once you have defined a skillset, you must map the output fields of any skill that directly contributes values to a given field in your search index.

Box 2: Yes

The definition is a custom skill that calls a web API as part of the enrichment process.

Box 3: No

For each organization identified by entity recognition, this skill calls a web API to find the description of that organization.

Reference:

https://docs.microsoft.com/en-us/azure/search/cognitive-search-output-field-mapping

Question 7:

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:

Correct Answer:

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 8:

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:

Correct Answer:

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:

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:

Correct Answer:

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 10:

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:

Correct Answer:

Question 11:

HOTSPOT

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.

Hot Area:

Correct Answer:

Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/what-are-cognitive-services

Question 12:

HOTSPOT

You have a Computer Vision resource named contoso1 that is hosted in the West US Azure region.

You need to use contoso1 to make a different size of a product photo by using the smart cropping feature.

How should you complete the API URL? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Hot Area:

Correct Answer:

westus.api.cognitive.microsoft.com

generateThumbnail

https://docs.microsoft.com/en-us/rest/api/computervision/3.1/generate-thumbnail/generate-thumbnail#examples POST https://westus.api.cognitive.microsoft.com/vision/v3.1/generateThumbnail?width=500andheight=500andsmartCropping=TrueOcp-Apim-Subscription-Key: {API key}

Question 13:

HOTSPOT

You are developing an application to recognize employees

Correct Answer:

A. True

B. True

C. True

B: see this example code from the documentation that uses PersonGroup of size 10,000 :

https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-add-faces

the question wants to trick you into thinking you need to use a LargePersonGroup for a size of 10,000 – but the documentation for it doesn\’t include this limitation or criteria:

https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-use-large-scale

Question 14:

HOTSPOT

You are building a bot 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:

Correct Answer:

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

Question 15:

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:

Correct Answer:

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

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