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.)
Actions
Train the application.
Publish the application.
Add a new application.
Add example utterances.
Add the prebuilt domain ToDo.
Answer Area
Correct Sequence of Actions
The correct order for the four actions in the answer area is:
Add a new application.
Add the prebuilt domain ToDo.
Add example utterances.
Train the application.
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?
From the Language Understanding portal, clone the model.
Export the model as an .lu file.
Create a new Speech service.
Create a new Language Understanding service.
Correct Answer
Export the model as an .lu file.
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.)
Actions
Add prebuilt domain models as required.
Validate the utterances logged for review
and modify the model.
Migrate authoring to an Azure resource
authoring key.
Enable active learning.
Enable log collection by using Log
Analytics.
Train and republish the Language
Understanding model.
Answer Area
Correct Sequence of Actions
The correct order for the three actions in the answer area is:
Enable log collection by using Log Analytics.
Validate the utterances logged for review and modify the model.
Train and republish the Language Understanding model.
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?
Access control (IAM)
Properties
Keys and Endpoint
Identity
Correct Answer
Keys and Endpoint
HOTSPOT
You are building a chatbot by using the Microsoft Bot Framework Composer.
AskForName > BeginDialog > Text
Show code
Prompt for text
Text input
Collection information. Ask for a word or sentence.
4
Learn more
BeginDialog
Begin dialog event
Bot Asks
User Input
Other
Property (string)
Bot Asks (Text)
What is your name?
user.name
Output Format
string
ex. =toUpper(this.value), S(toUpper(this.value))
A User Input (Text)
username = Input(Text)
Value
expression v
fx =coalesce(@user.Name.@personName)
Expected responses (intent: #Textinput_Response_GH5FTe)
Bot Asks (Number)
A
Hello S(user.name), how old are you?
User Input (Number)
user.age = Input(Number)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer Area
Statements
user.name is an entity.
The dialog asks for a user name and a user age and assigns appropriate values to the user. name and user. age properties.
The chatbot attempts to take the first non-null entity value for userName or personName and assigns the value to user. name.
Answer Area
Statements and their correct answers:
user.name is an entity.
No
The dialog asks for a user name and a user age and assigns appropriate values to the user.name and user.age properties.
Yes
The chatbot attempts to take the first non-null entity value for userName or personName and assigns the value to user.name.
Yes
- 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.
protected override async Task OnMembersAddedAsync(IList<ChannelAccount>
membersAdded, ITurnContext<IConversationUpdateActivity> turnContext,
CancellationToken cancellationToken)</IConversationUpdateActivity></ChannelAccount>
-
foreach (var member in membersAdded)
if (member. Id != turnContext.Activity. Recipient. Id)
await turnContext.SendActivityAsync($”Hi there - (member.Name).
(WelcomeMessage}”, cancellationToken: cancellationToken);
-
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth
one point.
Answer Area
Statements
Yes
No
OnMembersAddedAsync will be triggered when a user joins the conversation.
When a new user joins the conversation, the existing users in the conversation will see the chatbot greeting.
OnMembersAddedAsync will be initialized when a user sends a message.
Answer Area
Statements and their correct answers:
OnMembersAddedAsync will be triggered when a user joins the conversation.
Yes
When a new user joins the conversation, the existing users in the conversation will see the chatbot greeting.
No
OnMembersAddedAsync will be initialized when a user sends a message.
No
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.
Answer Area
Statements
$ {user. name } retrieves the user name by using a prompt.
Greet () is the name of the language generation template.
$ {Greeting () } is a reference to a template in the language generation file.
Answer Area
Statements and their correct answers:
${user.name} retrieves the user name by using a prompt.
No
Greet() is the name of the language generation template.
Yes
${Greeting()} is a reference to a template in the language generation file.
Yes
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));</UserProfile>
var conversationStateAccessors =
_conversationState.CreateProperty<ConversationData>(nameof(ConversationData));</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.
Answer Area
Statements
The code will create and maintain the UserProfile object
in the underlying storage layer.
The code will create and maintain the ConversationData
object in the underlying storage layer.
The UserProfile and ConversationData objects will
persist when the Bot Framework runtime terminates.
Answer Area
Statements and their correct answers:
The code will create and maintain the UserProfile object in the underlying storage layer.
Yes
The code will create and maintain the ConversationData object in the underlying storage layer.
Yes
The UserProfile and ConversationData objects will persist when the Bot Framework runtime terminates.
No
HOTSPOT
You are building a chatbot that will provide information to users as shown in the following exhibit.
Passengers
Sarah Hum
Jeremy Goldberg
Evan Litvak
2 Stops
Tue, May 30, 2017 10:25 PM
San Francisco ——————> San Francisco
Amsterdam Amsterdam
SFO SFO
AMS AMS
Non-Stop
Fri, Jun 2, 2017 11:55 PM
San Francisco ———————–> San Francisco
Amsterdam ——————-> Amsterdam
SFO ——————–> SFO
AMS ——————–> AMS
Total $4,032.54
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.
Answer Area
The chatbot is showing [answer choice].
an Adaptive Card
a Hero Card
a Thumbnail Card
The card includes [answer choice].
an action set
an image
an image group
media
Answer Area
Statements and their correct answers:
The chatbot is showing [answer choice].
an Adaptive Card
The card includes [answer choice].
an action set
Testlet 2
Case study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
Existing Environment
A company named Wide World Importers is developing an e-commerce platform.
You are working with a solutions architect to design and implement the features of the e-commerce platform. The platform will use microservices and a serverless environment built on Azure.
Wide World Importers has a customer base that includes English, Spanish, and Portuguese speakers.
Applications
Wide World Importers has an App Service plan that contains the web apps shown in the following table.
Name
Product Management Description
An app used by employees to create and manage products. The app
and the expected inputs from the employees are in English.
Inventory Tracking Description
An app used by employees to manage inventory when dispatching
orders, receiving refunds, and receiving consignments from suppliers.
Azure Resources
You have the following resources:
- An Azure Active Directory (Azure AD) tenant
- The tenant supports internal authentication.
- All employees belong to a group named AllUsers.
- Senior managers belong to a group named LeadershipTeam.
- An Azure Functions resource
- A function app posts to Azure Event Grid when stock levels of a product change between OK, Low Stock, and Out of Stock. The function app uses the Azure Cosmos DB change feed.
- An Azure Cosmos DB account
- The account uses the Core (SQL) API.
- The account stores data for the Product Management app and the Inventory Tracking app.
- An Azure Storage account
- The account contains blob containers for assets related to products.
- The assets include images, videos, and PDFs.
- An Azure Cognitive Services resource named wwics
- A Video Indexer resource named wwivi
Requirements
Business Goals
Wide World Importers wants to leverage AI technologies to differentiate itself from its competitors.
Planned Changes
Wide World Importers plans to start the following projects:
- A product creation project: Help employees create accessible and multilingual product entries, while expediting product entry creation.
- A smart e-commerce project: Implement an Azure Cognitive Search solution to display products for customers to browse.
- A shopping on-the-go project: Build a chatbot that can be integrated into smart speakers to support customers.
Business Requirements
Wide World Importers identifies the following business requirements for all the projects:
- Provide a multilingual customer experience that supports English, Spanish, and Portuguese.
- Whenever possible, scale based on transaction volumes to ensure consistent performance.
- Minimize costs.
Governance and Security Requirements
Wide World Importers identifies the following governance and security requirements:
- Data storage and processing must occur in datacenters located in the United States.
- Azure Cognitive Services must be inaccessible directly from the internet.
Accessibility Requirements
Wide World Importers identifies the following accessibility requirements:
- All images must have relevant alt text.
- All videos must have transcripts that are associated to the video and included in product descriptions.
- Product descriptions, transcripts, and all text must be available in English, Spanish, and Portuguese.
Product Creation Requirements
Wide World Importers identifies the following requirements for improving the Product Management app:
- Minimize how long it takes for employees to create products and add assets.
- Remove the need for manual translations.
Smart E-Commerce Requirements
Wide World Importers identifies the following requirements for the smart e-commerce project:
- Ensure that the Cognitive Search solution meets a Service Level Agreement (SLA) of 99.9% availability for searches and index writes.
- Provide users with the ability to search insight gained from the images, manuals, and videos associated with the products.
- Support autocompletion and autosuggestion based on all product name variants.
- Store all raw insight data that was generated, so the data can be processed later.
- Update the stock level field in the product index immediately upon changes.
- Update the product index hourly.
Shopping On-the-Go Requirements
Wide World Importers identifies the following requirements for the shopping on-the-go chatbot:
- Answer common questions.
- Support interactions in English, Spanish, and Portuguese.
- Replace an existing FAQ process so that all Q&A is managed from a central location.
- Provide all employees with the ability to edit Q&As. Only senior managers must be able to publish updates.
- Support purchases by providing information about relevant products to customers. Product displays must include images and warnings when stock levels are low or out of stock.
Product JSON Sample
You have the following JSON sample for a product.
{
“sku”: “b1”,
“name”: {
“en”: “Bicycle”,
“es”: “Bicicleta”,
“pt”: “Bicicleta”
},
“stocklevel”: “Out of Stock”,
“description”: {
“en”: “Bicycle”,
“es”: “Bicicleta”,
“pt”: “Bicicleta”
},
“image”: {
“uri”: “https://upload.worldwideimporters.org/bicycle.jpg”,
“alttext”: {
“en”: “Bicycle”,
“es”: “Bicicleta”,
“pt”: “Bicicleta”
}
},
“createdUtc”: “2020-02-14T06:08:39Z”,
“language”: “en”
}
HOTSPOT
You are developing the shopping on-the-go project.
You are configuring access to the QnA Maker resources.
Which role should you assign to AllUsers and LeadershipTeam? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Answer Area
AllUsers:
Cognitive Service User
Contributor
Owner
QnA Maker Editor
QnA Maker Read
LeadershipTeam:
Cognitive Service User
Contributor
Owner
QnA Maker Editor
QnA Maker Read
Answer Area
AllUsers: QnA Maker Editor
LeadershipTeam: Contributor
DRAG DROP
You have 100 chatbots that each has its own Language Understanding model.
Frequently, you must add the same phrases to each model.
You need to programmatically update the Language Understanding models to include the new phrases.
How should you complete the code? To answer, drag the appropriate values to the correct targets. Each value 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. NOTE: Each correct selection is worth one point.
Values
AddPhraseListAsync
Phraselist
Phrases
SavePhraselistAsync
UploadPhraseListAsync
Answer Area
var phraselistId = await client.Features.————————
(appId, versionId, new ——————————
{
EnabledForAllModels = false,
IsExchangeable = true,
Name = “PL1”,
Phrases = “item1, item2, item3, item4, item5”
);
Correct Selections for the Drag-and-Drop Targets
First blank (after client.Features.): AddPhraseListAsync
Second blank (after new ): Phraselist
DRAG DROP
You plan to use a Language Understanding application named app1 that is deployed to a container.
App1 was developed by using a Language Understanding authoring resource named lu1.
App1 has the versions shown in the following table.
Version | Trained date | Published date
V1.2 | None | None
V1.1 | 2020-10-01 | None
V1.0 | 2020-09-01 | 2020-09-15
You need to create a container that uses the latest deployable version of app1.
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.)
Actions Answer Area
Run a container that has version
set as an environment variable.
Export the model by using the
Export as JSON option.
Select v1.1 of app1.
Run a container and mount the
model file.
Select v1.0 of app1.
Export the model by using the
Export for containers (GZIP) option.
Select v1.2 of app1.
Correct Actions and Sequence for the Answer Area
To create a container that uses the latest deployable version of the Language Understanding (LUIS) application app1, the following three actions should be performed in sequence:
Select v1.0 of app1.
Export the model by using the Export for containers (GZIP) option.
Run a container and mount the model file.
You need to build a chatbot that meets the following requirements:
- Supports chit-chat, knowledge base, and multilingual models
- Performs sentiment analysis on user messages
- Selects the best language model automatically
What should you integrate into the chatbot?
QnA Maker, Language Understanding, and Dispatch
Translator, Speech, and Dispatch
Language Understanding, Text Analytics, and QnA Maker
Text Analytics, Translator, and Dispatch
Correct Answer
Language Understanding, Text Analytics, and QnA Maker
Your company wants to reduce how long it takes for employees to log receipts in expense reports. All the receipts are in English.
You need to extract top-level information from the receipts, such as the vendor and the transaction total.
The solution must minimize development effort.
Which Azure Cognitive Services service should you use?
Custom Vision
Personalizer
Form Recognizer
Computer Vision
Correct Answer
Form Recognizer
HOTSPOT
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.
Answer Area
https://management.azure.com/subscriptions/
PATCH
POST
PUT
xxxx-xxxx-
xxxxxxxxxxxx/resourceGroups/RG1/providers/Microsoft.CognitiveServices/
accounts/CS1?api-version=2017-04-18
{
“location”: “West US”,
“kind”: “
CognitiveServices
ComputerVision
TextAnalytics
“sku”: {
“name”: “SO”
},
“properties”: (),
“identity”: {
“type”: “SystemAssigned”
}
}
Correct Selections for the Hotspot Answer Area
To create a new Azure resource that supports sentiment analysis, optical character recognition (OCR), uses a single key and endpoint for multiple services, consolidates billing, and supports future use of Computer Vision, the HTTP request should be completed as follows:
HTTP Method: POST
Kind: CognitiveServices
You are developing a new sales system that will process the video and text from a public-facing website.
You plan to monitor the sales system to ensure that it provides equitable results regardless of the user’s
location or background.
Which two responsible AI principles provide guidance to meet the monitoring requirements? Each correct answer presents part of the solution. (Choose two.)
NOTE: Each correct selection is worth one point.
transparency
fairness
inclusiveness
reliability and safety
privacy and security
Correct Answer
Fairness and Inclusiveness
DRAG DROP
You plan to use containerized versions of the Anomaly Detector API on local devices for testing and in on-premises datacenters.
You need to ensure that the containerized deployments meet the following requirements:
- Prevent billing and API information from being stored in the command-line histories of the devices that run the container.
- Control access to the container images by using Azure role-based access control (Azure RBAC).
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.)
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Actions
Create a custom Dockerfile.
Pull the Anomaly Detector container image.
Distribute a docker run script.
Push the image to an Azure container registry.
Build the image.
Push the image to Docker Hub.
Answer Area
Correct Actions and Sequence for the Answer Area
To deploy containerized versions of the Anomaly Detector API on local devices and on-premises datacenters while meeting the requirements of preventing billing and API information from being stored in command-line histories and controlling access using Azure role-based access control (Azure RBAC), the following four actions should be performed in sequence:
Create a custom Dockerfile.
Build the image.
Push the image to an Azure container registry.
Pull the Anomaly Detector container image.
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.
Answer Area
docker run – rm -it -p 5000:5000 – memory 8g – cpus 1 \
<dropdown>
http://contoso.blob.core.windows.net
https://contoso.cognitiveservices.azure.com
mcr.microsoft.com/azure-cognitive-services/textanalytics/keyphrase
mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment
Eula=accept
Billing=<dropdown>
http://contoso.blob.core.windows.net
https://contoso.cognitiveservices.azure.com
mcr.microsoft.com/azure-cognitive-services/textanalytics/keyphrase
mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment
ApiKey=xxx
</dropdown></dropdown>
Correct Selections for the Hotspot Answer Area
To run the containerized version of the Azure Cognitive Services Text Analytics Sentiment Analysis container on an Azure virtual machine using Docker, the docker run command should be completed as follows:
First dropdown (image name): mcr.microsoft.com/azure-cognitive-services/textanalytics/sentiment
Second dropdown (Billing value): https://contoso.cognitiveservices.azure.com
You have the following C# method for creating Azure Cognitive Services resources programmatically.
static void create_resource (CognitiveServicesManagementClient client, string
resource name, string kind, string account_tier, string location)
{
CognitiveServicesAccount parameters =
new CognitiveServicesAccount (null, null, kind, location, resource_name,
new CognitiveServicesAccountProperties (), new Sku(account_tier));
var result = client.Accounts.Create (resource_group_name, account_tier,
parameters);
}
You need to call the method to create a free Azure resource in the West US Azure region. The resource will be used to generate
captions of images automatically.
Which code should you use?
create_resource(client, “res1”, “ComputerVision”, “FO”, “westus”)
create_resource(client, “res1”, “CustomVision.Prediction”, “FO”, “westus”)
create_resource(client, “res1”, “ComputerVision”, “SO”, “westus”)
create_resource(client, “res1”, “CustomVision.Prediction”, “SO”, “westus”)
create_resource(client, “res1”, “ComputerVision”, “F0”, “westus”)
You successfully run the following HTTP request.
POST https://management.azure.com/subscriptions/18c51a87-3a69-47a8-aedc-a54745f708a1/resourceGroups/RG1/providers/Microsoft.CognitiveServices/ accounts/contosol/regenerateKey?api-version=2017-04-18 Body{“keyName”: “Key2”}
What is the result of the request?
A key for Azure Cognitive Services was generated in Azure Key Vault.
A new query key was generated.
The primary subscription key and the secondary subscription key were rotated.
The secondary subscription key was reset.
Correct Answer
The secondary subscription key was reset.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You develop an application to identify species of flowers by training a Custom Vision model. You receive images of new flower species.
You need to add the new images to the classifier.
Solution: You add the new images and labels to the existing model. You retrain the model, and then publish the model.
Does this meet the goal?
Yes
No
Yes
- DRAG DROP
You are developing a call to the Face API. The call must find similar faces from an existing list named employeefaces. The
employeefaces list contains 60,000 images.
How should you complete the body of the HTTP request? To answer, drag the appropriate values to the correct targets. Each value
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. NOTE:
Each correct selection is worth one point.
Values
“faceListId”
“LargeFaceListId”
“matchPerson”
“matchFace”
Answer Area
{
“faceId”: “18c51a87-3a69-47a8-aedc-a54745f708a1”,
—————: “employeefaces”,
“maxNumOfCandidatesReturned”: 1,
“mode”: —————
}
largeFaceListId
matchFace
{
“faceId”: “18c51a87-3a69-47a8-aedc-a54745f708a1”,
“largeFaceListId”: “employeefaces”,
“maxNumOfCandidatesReturned”: 1,
“mode”: “matchFace”
}
DRAG DROP
You are developing the smart e-commerce project.
You need to design the skillset to include the contents of PDFs in searches.
How should you complete the skillset design diagram? To answer, drag the appropriate services to the correct stages. Each service 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. NOTE: Each correct selection is worth one point.
Services
Azure Blob storage
Custom Vision API
Azure Files
Language Understanding API
Translator API
Computer Vision API
Azure Cosmos DB
Answer Area
Source Cracking Preparation Destination
———- —- > ———- —- > —————– —- >
Correct Answer:
Source: Azure Blob Storage
Cracking: Computer Vision API
Preparation: None
Destination: Azure Cosmos DB
Answer Area:
Azure Blob Storage —-> Computer Vision API —-> Azure Cosmos DB
You are building a natural language model.
You need to enable active learning.
What should you do?
Add show-all-intents=true to the prediction endpoint query.
Enable speech priming.
Add log=true to the prediction endpoint query.
Enable sentiment analysis.
Correct Answer: Add log=true to the prediction endpoint query.
