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Microsoft Certified: Azure AI Fundamentals
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Microsoft Azure AI Fundamentals Questions and Answers

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Questions # 71:

You need to develop a chatbot for a website. The chatbot must answer users’ questions based on the information in the following documents:

A product troubleshooting guide in a Microsoft Word document

A frequently asked questions (FAQ) list on a webpage

Which service should you use to process the documents?

Options:

Azure Bot Service

Language Understanding

Text Analytics

QnA Maker

Answer

Explanation

[Reference:, https://docs.microsoft.com/en-us/azure/cognitive-services/QnAMaker/Overview/overview, , , ]

Questions # 72:

To complete the sentence, select the appropriate option in the answer area.

Question # 72

Options:

Answer

Answer:

Explanation

[Reference:, https://azure.microsoft.com/en-gb/services/cognitive-services/speech-to-text/#features, , Speech recognition means Speech to Text. In the above example as a person speaks the words are converted into text of the same language. Hence Speech to Text also called Speech recognition is the right answer., Speech recognition - the ability to detect and interpret spoken input., Speech synthesis - the ability to generate spoken output., https://docs.microsoft.com/en-us/learn/modules/recognize-synthesize-speech/1-introduction, , , ]

Questions # 73:

You are developing a solution that uses the Text Analytics service.

You need to identify the main talking points in a collection of documents.

Which type of natural language processing should you use?

Options:

entity recognition

key phrase extraction

sentiment analysis

language detection

Answer

Explanation

Broad entity extraction: Identify important concepts in text, including key

Key phrase extraction/ Broad entity extraction: Identify important concepts in text, including key phrases and named entities such as people, places, and organizations.

[Reference:, https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing, , , , ]

Questions # 74:

In which scenario should you use key phrase extraction?

Options:

translating a set of documents from English to German

generating captions for a video based on the audio track

identifying whether reviews of a restaurant are positive or negative

identifying which documents provide information about the same topics

Answer

Questions # 75:

You use natural language processing to process text from a Microsoft news story.

You receive the output shown in the following exhibit.

Question # 75

Which type of natural languages processing was performed?

Options:

entity recognition

key phrase extraction

sentiment analysis

translation

Answer

Explanation

https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview

You can provide the Text Analytics service with unstructured text and it will return a list of entities in the text that it recognizes. You can provide the Text Analytics service with unstructured text and it will return a list of entities in the text that it recognizes. The service can also provide links to more information about that entity on the web. An entity is essentially an item of a particular type or a category; and in some cases, subtype, such as those as shown in the following table.

https://docs.microsoft.com/en-us/learn/modules/analyze-text-with-text-analytics-service/2-get-started-azure

Questions # 76:

You build a QnA Maker bot by using a frequently asked questions (FAQ) page.

You need to add professional greetings and other responses to make the bot more user friendly.

What should you do?

Options:

Increase the confidence threshold of responses

Enable active learning

Create multi-turn questions

Add chit-chat

Answer

Explanation

[Reference:, https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/chit-chat-knowledge-base?tabs=v1, , , ]

Questions # 77:

What can be used to complete a paragraph based on a sentence provided by a user?

Options:

Azure Al Language

Azure OpenAI

Azure Machine Learning

Azure Al Vision

Answer

Questions # 78:

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 # 78

Options:

Answer

Answer:

Explanation

Clustering is a machine learning task that is used to group instances of data into clusters that contain similar characteristics. Clustering can also be used to identify relationships in a dataset

Regression is a machine learning task that is used to predict the value of the label from a set of related features.

[Reference:, https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks, , , ]

Questions # 79:

You have an Azure Machine Learning model that predicts product quality. The model has a training dataset that contains 50,000 records. A sample of the data is shown in the following table.

Question # 79

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 # 79

Options:

Answer

Answer:

Questions # 80:

You need to develop a web-based AI solution for a customer support system. Users must be able to interact with a web app that will guide them to the best resource or answer.

Which service should you integrate with the web app to meet the goal?

Options:

Azure Al Language Service

Face

Azure Al Translator

Azure Al Custom Vision

Answer

Explanation

QnA Maker is a cloud-based API service that lets you create a conversational question-and-answer layer over your existing data. Use it to build a knowledge base by extracting questions and answers from your semistructured content, including FAQs, manuals, and documents. Answer users’ questions with the best answers from the QnAs in your knowledge base—automatically. Your knowledge base gets smarter, too, as it

continually learns from user behavior.

[Reference:, https://azure.microsoft.com/en-us/services/cognitive-services/qna-maker/, , , ]

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