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Topics of AI-102: Designing and Implementing an Azure AI Solution Exam

Candidates should apprehend the examination topics before they begin of preparation. because it’ll extremely facilitate them in touch the core. Our AI-102 dumps will include the following topics:

1. Analyze solution requirements (25-30%)

Recommend Cognitive Services APIs to meet business requirements

• Identify automation requirements
• Select the appropriate data processing technologies
• Identify components and technologies required to connect service endpoints
• Select the processing architecture for a solution
• Select the appropriate AI models and services

Map security requirements to tools, technologies, and processes

• Identify auditing requirements
• Identify which users and groups have access to information and interfaces
• Identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements
• Identify appropriate tools for a solution

Select the software, services, and storage required to support a solution

• Identify integration points with other Microsoft services
• Identify storage required to store logging, bot state data, and Cognitive Services output
• Identify appropriate services and tools for a solution

2. Design AI solutions (40-45%)

Design solutions that include one or more pipelines

• Design pipelines that call Azure Machine Learning models
• Design pipelines that use AI apps
• Design a strategy for ingest and egress data
• Define an AI application workflow process
• Select an AI solution that meet cost constraints
• Design the integration point between multiple workflows and pipelines

Design solutions that uses Cognitive Services

• Design solutions that use vision, speech, language, knowledge, search, and anomaly detection APIs

Design solutions that implement the Bot Framework

• Design bots that integrate with channels
• Integrate bots with Azure app services and Azure Application Insights
• Integrate bots and AI solutions
• Design bot services that use Language Understanding (LUIS)

Design the compute infrastructure to support a solution

• Identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure
• Select a compute solution that meets cost constraints
• Identify whether to create a GPU, FPGA, or CPU-based solution

Design for data governance, compliance, integrity, and security

• Ensure appropriate governance of data
• Ensure that data adheres to compliance requirements defined by your organization
• Define how users and applications will authenticate to AI services
• Design strategies to ensure that the solution meets data privacy regulations and industry standards
• Design a content moderation strategy for data usage within an AI solution

3. Implement and monitor AI solutions (25-30%)

Implement an AI workflow

• Implement data logging processes
• Define and construct interfaces for custom AI services
• Manage the flow of data through the solution components
• Develop AI pipelines
• Develop streaming solutions
• Create solution endpoints

Integrate AI services with solution components

• Implement Azure Search in a solution
• Configure integration with Cognitive Services
• Configure prerequisite components to allow connectivity to the Bot Framework
• Configure prerequisite components and input datasets to allow the consumption of Cognitive Services APIs

Monitor and evaluate the AI environment

• Identify the differences between expected and actual workflow throughput
• Identify the differences between KPIs, reported metrics, and root causes of the differences
• Maintain an AI solution for continuous improvement
• Recommend changes to an AI solution based on performance data
• Monitor AI components for availability

 

NEW QUESTION 18
You are building an Azure Weblob that will create knowledge bases from an array of URLs.
You instantiate a QnAMakerClient object that has the relevant API keys and assign the object to a variable named client.
You need to develop a method to create the knowledge bases.
Which two actions should you include in the method? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

• A. Call the client. Knowledgebase. CreateAsync method.
• B. Create a list of FileDTO objects that represents data from the WebJob.
• C. Create a CreaceKbDTO object.
• D. Create a list of QnADTO objects that represents data from the WebJob.

Answer: B,D

Explanation:
Reference:
https://docs.microsoft.com/en-us/rest/api/cognitiveservices-qnamaker/qnamaker4.0/knowledgebase/create

 

NEW QUESTION 19
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.

Answer:

Explanation:

Explanation:
Box 1: AddPhraseListAsync
Example: Add phraselist feature
var phraselistId = await client.Features.AddPhraseListAsync(appId, versionId, new PhraselistCreateObject
{
EnabledForAllModels = false,
IsExchangeable = true,
Name = "QuantityPhraselist",
Phrases = "few,more,extra"
});
Box 2: PhraselistCreateObject
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/client-libraries-rest-api

 

NEW QUESTION 20
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.

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

 

NEW QUESTION 21
You run the following command.

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

Answer:

Explanation:

Explanation
Text Description automatically generated

Box 1: Yes
http://localhost:5000/status
: Also requested with GET, this verifies if the api-key used to start the container is valid without causing an endpoint query.
Box 2: Yes
The command saves container and LUIS logs to output mount at C:\output, located on container host
Box 3: Yes
http://localhost:5000/swagger
: The container provides a full set of documentation for the endpoints and a Try it out feature. With this feature, you can enter your settings into a web-based HTML form and make the query without having to write any code. After the query returns, an example CURL command is provided to demonstrate the HTTP headers and body format that's required.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-container-howto

 

NEW QUESTION 22
You need to upload speech samples to a Speech Studio project. How should you upload the samples?

• A. Upload a .zip file that contains a collection of audio files in the .wav format and a corresponding text transcript file.
• B. Upload individual audio files in the .wma format.
• C. Upload individual audio files in the FLAC format and manually upload a corresponding transcript in Microsoft Word format.
• D. Combine the speech samples into a single audio file in the .wma format and upload the file.

Answer: A

Explanation:
Explanation
To upload your data, navigate to the Speech Studio . From the portal, click Upload data to launch the wizard and create your first dataset. You'll be asked to select a speech data type for your dataset, before allowing you to upload your data.
The default audio streaming format is WAV
Use this table to ensure that your audio files are formatted correctly for use with Custom Speech:

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/how-to-custom-speech-test-and-train

 

NEW QUESTION 23
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.

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.)

Answer:

Explanation:

Step 1: Export the model using the Export for containers (GZIP) option.
Export versioned app's package from LUIS portal
The versioned app's package is available from the Versions list page.
* Sign on to the LUIS portal.
* Select the app in the list.
* Select Manage in the app's navigation bar.
* Select Versions in the left navigation bar.
* Select the checkbox to the left of the version name in the list.
* Select the Export item from the contextual toolbar above the list.
* Select Export for container (GZIP).
* The package is downloaded from the browser.

Step 2: Select v1.1 of app1.
A trained or published app packaged as a mounted input to the container with its associated App ID.
Step 3: Run a contain and mount the model file.
Run the container, with the required input mount and billing settings.
nce:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-container-howto

 

NEW QUESTION 24
You have the following C# method for creating Azure Cognitive Services resources programmatically.

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?

• A. create_resource(client, "res1", "CustomVision.Prediction", "S0", "westus")
• B. create_resource(client, "res1", "ComputerVision", "S0", "westus")
• C. create_resource(client, "res1", "CustomVision.Prediction", "F0", "westus")
• D. create_resource(client, "res1", "ComputerVision", "F0", "westus")

Answer: C

Explanation:
Explanation
Many of the Cognitive Services have a free tier you can use to try the service. To use the free tier, use F0 as the SKU for your resource.
There are two tiers of keys for the Custom Vision service. You can sign up for a F0 (free) or S0 (standard) subscription through the Azure portal.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/cognitive-services-apis-create-account-client-library?p
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/limits-and-quotas

 

NEW QUESTION 25
You develop a test method to verify the results retrieved from a call to the Computer Vision API. The call is used to analyze the existence of company logos in images. The call returns a collection of brands named brands.
You have the following code segment.

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:

Explanation:

Explanation:
Box 1: Yes
Box 2: Yes
If several logs are detected, or the logo image and the stylized brand name are detected as two separate logos, it starts numbering them from the bottom-left corner.
Box 3: No
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-brand-detection

 

NEW QUESTION 26
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.

Answer:

Explanation:
Graphical user interface, text, application Description automatically generated

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

 

NEW QUESTION 27
You are developing the smart e-commerce project.
You need to implement autocompletion as part of the Cognitive Search solution.
Which three actions should you perform? Each correct answer presents part of the solution. (Choose three.) NOTE: Each correct selection is worth one point.

• A. Make API queries to the autocomplete endpoint and include suggesterName in the body.
• B. Use the default standard Lucene analyzer ("analyzer": null) or a language analyzer (for example, "analyzer": "en.Microsoft") on the field.
• C. Add a suggester that has the three product name fields as source fields.
• D. Make API queries to the search endpoint and include the product name fields in the searchFields query parameter.
• E. Set the analyzer property for the three product name variants.
• F. Set the searchAnalyzer property for the three product name variants.
• G. Add a suggester for each of the three product name fields.

Answer: A,C,E

Explanation:
Scenario: Support autocompletion and autosuggestion based on all product name variants.
A: Call a suggester-enabled query, in the form of a Suggestion request or Autocomplete request, using an API. API usage is illustrated in the following call to the Autocomplete REST API.
POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2020-06-30
{
"search": "minecraf",
"suggesterName": "sg"
}
B: In Azure Cognitive Search, typeahead or "search-as-you-type" is enabled through a suggester. A suggester provides a list of fields that undergo additional tokenization, generating prefix sequences to support matches on partial terms. For example, a suggester that includes a City field with a value for "Seattle" will have prefix combinations of "sea", "seat", "seatt", and "seattl" to support typeahead.
Reference:
https://docs.microsoft.com/en-us/azure/search/index-add-suggesters

 

NEW QUESTION 28
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
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 have an Azure Cognitive Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Cognitive Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You add indexes.
Does this meet the goal?

• A. No
• B. Yes

Answer: A

Explanation:
Explanation
Instead, you could migrate to a Cognitive Search service that uses a higher tier.
Note: A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing-based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis

 

NEW QUESTION 29
You need to implement a table projection to generate a physical expression of an Azure Cognitive Search index.
Which three properties should you specify in the skillset definition JSON configuration table node? Each correct answer presents part of the solution. (Choose three.) NOTE: Each correct selection is worth one point.

• A. source
• B. dataSource
• C. dataSourceConnection
• D. tableName
• E. generatedKeyName

Answer: A,D,E

 

NEW QUESTION 30
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. The secondary subscription key was reset.
• B. A new query key was generated.
• C. The primary subscription key and the secondary subscription key were rotated.
• D. A key for Azure Cognitive Services was generated in Azure Key Vault.

Answer: B

Explanation:
Accounts - Regenerate Key regenerates the specified account key for the specified Cognitive Services account.
Syntax:
POST https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/ providers/Microsoft.CognitiveServices/accounts/{accountName}/regenerateKey?api-version=2017-04-18 Reference:
https://docs.microsoft.com/en-us/rest/api/cognitiveservices/accountmanagement/accounts/regeneratekey

 

NEW QUESTION 31
You use the Custom Vision service to build a classifier.
After training is complete, you need to evaluate the classifier.
Which two metrics are available for review? Each correct answer presents a complete solution. (Choose two.) NOTE: Each correct selection is worth one point.

• A. F-score
• B. area under the curve (AUC)
• C. recall
• D. precision
• E. weighted accuracy

Answer: C,D

Explanation:
Custom Vision provides three metrics regarding the performance of your model: precision, recall, and AP.
Reference:
https://www.tallan.com/blog/2020/05/19/azure-custom-vision/

 

NEW QUESTION 32
You are building a Language Understanding model for an e-commerce platform. You need to construct an entity to capture billing addresses.
Which entity type should you use for the billing address?

• A. list
• B. machine learned
• C. Regex
• D. geographyV2
• E. Pattern.any

Answer: C

Explanation:
A regular expression entity extracts an entity based on a regular expression pattern you provide. It ignores case and ignores cultural variant. Regular expression is best for structured text or a predefined sequence of alphanumeric values that are expected in a certain format. For example:

Incorrect Answers:
C: 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. GeographyV2 entity is supported in English culture.
The geographical locations have subtypes:

D: Pattern.any is a variable-length placeholder used only in a pattern's template utterance to mark where the entity begins and ends.
E: A list entity represents a fixed, closed set of related words along with their synonyms. You can use list entities to recognize multiple synonyms or variations and extract a normalized output for them. Use the recommend option to see suggestions for new words based on the current list.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-entity-types

 

NEW QUESTION 33
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.

Answer:

Explanation:

Explanation:
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 were 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

 

NEW QUESTION 34
You are building a model that will be used in an iOS app.
You have images of cats and dogs. Each image contains either a cat or a dog.
You need to use the Custom Vision service to detect whether the images is of a cat or a dog.
How should you configure the project in the Custom Vision portal? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:
Graphical user interface, text, application, email Description automatically generated

Box 1: Classification
Box 2: Multiclass
A multiclass classification project is for classifying images into a set of tags, or target labels. An image can be assigned to one tag only.
Box 3: General
General: Optimized for a broad range of image classification tasks. If none of the other specific domains are appropriate, or if you're unsure of which domain to choose, select one of the General domains.
Reference:
https://cran.r-project.org/web/packages/AzureVision/vignettes/customvision.html

 

NEW QUESTION 35
You need to upload speech samples to a Speech Studio project. How should you upload the samples?

• A. Upload a .zip file that contains a collection of audio files in the .wav format and a corresponding text transcript file.
• B. Upload individual audio files in the .wma format.
• C. Upload individual audio files in the FLAC format and manually upload a corresponding transcript in Microsoft Word format.
• D. Combine the speech samples into a single audio file in the .wma format and upload the file.

Answer: A

Explanation:
To upload your data, navigate to the Speech Studio . From the portal, click Upload data to launch the wizard and create your first dataset. You'll be asked to select a speech data type for your dataset, before allowing you to upload your data.
The default audio streaming format is WAV
Use this table to ensure that your audio files are formatted correctly for use with Custom Speech:

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/how-to-custom-speech-test-and-train

 

NEW QUESTION 36
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.

Answer:

Explanation:

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

 

NEW QUESTION 37
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