Designing and Implementing a Microsoft Azure AI Solution328 questions across 33 pages are complete and free, with no account or card.
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You have a Conversational Language Understanding model. You export the model as a JSON file. The following is a sample of the file.
What represents the Weather.Historic entity in the sample utterance?
Answer: B
"average amount of rain by month in Chicago last year" . The question has mistake, should start position - end position are 23 - 31.
Source: Adapted from community discussion — james2033
You are building a chatbot by using Microsoft Bot Framework Composer. You need to configure the chatbot to present a list of available options. The solution must ensure that an image is provided for each option. Which two features should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: DE
To configure the chatbot to present a list of available options with images, you should use the following features: D. An adaptive card: Adaptive cards are a flexible, customizable way to present rich, interactive content within a chatbot conversation. You can use adaptive cards to display a list of available options, along with images and other interactive elements, such as buttons or inputs. E. A dialog: Dialogs are used to manage and organize the conversation flow in your chatbot. You can create a dialog that is responsible for presenting the list of available options using an adaptive card. The dialog can be triggered when needed, and it can handle the user's selection of an option.
Source: Adapted from community discussion — kail85
You are building a chatbot. You need to configure the bot to guide users through a product setup process. Which type of dialog should you use?
Answer: C
C is the answer. https://learn.microsoft.com/en-us/azure/bot-service/bot-builder-concept-dialog?view=azure-bot-service-4.0#dialog-types The dialogs library provides a few types of dialogs to make your bot's conversations easier to manage. - waterfall dialog Defines a sequence of steps, allowing your bot to guide a user through a linear process. These are typically designed to work within the context of a component dialog.
Source: Adapted from community discussion — zellck
You have a chatbot that was built by using Microsoft Bot Framework and deployed to Azure. You need to configure the bot to support voice interactions. The solution must support multiple client apps. Which type of channel should you use?
Answer: C
C is the answer. https://learn.microsoft.com/en-us/azure/bot-service/bot-service-channel-directline?view=azure-bot-service-4.0 The Bot Framework offers multiple channels with the Direct Line branding. It's important that you select the version that best fits the conversational AI experience you're designing. - Direct Line Speech. It provides text-to-speech and speech-to-text services within the channel. It allows a client to stream audio directly to the channel which will then be converted to text and sent to the bot. Direct Line Speech can also convert text messages from the bot into audio messages spoken by an AI-powered voice. Combined, this makes Direct Line Speech capable of having audio only conversations with clients.
Source: Adapted from community discussion — zellck
You are building a bot by using Microsoft Bot Framework. You need to configure the bot to respond to spoken requests. The solution must minimize development effort. What should you do?
Answer: A
A. Deploy the bot to Azure and register the bot with a Direct Line Speech channel. To enable the bot to respond to spoken requests with minimal development effort, you should deploy the bot to Azure and register the bot with a Direct Line Speech channel. Direct Line Speech provides an integrated speech and bot experience without requiring additional development. It combines both the speech-to-text and text-to-speech capabilities with the bot's logic to handle spoken requests and generate spoken responses.
Source: Adapted from community discussion — kail85
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 a chatbot that uses question answering in Azure Cognitive Service for Language. Users report that the responses of the chatbot lack formality when answering spurious questions. You need to ensure that the chatbot provides formal responses to spurious questions. Solution: From Language Studio, you remove all the chit-chat question and answer pairs, and then retrain and republish the model. Does this meet the goal?
Answer: B
The given answer Correct. Removing all chitchat QA pairs will not solve the problem of lack of formality. To solve the issue, change the chitchat source to qna_chitchat_professional.tsv Check out https://learn.microsoft.com/en-us/azure/ai-services/language-service/question-answering/concepts/best-practices#choosing-a-personality
Source: Adapted from community discussion — Lion007
HOTSPOT - You are building a chatbot. You need to use the Content Moderator service to identify messages that contain sexually explicit language. Which section in the response from the service will contain the category score, and which category will be assigned to the message? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.
Answer: See figure below
1. Classification 2. 1 https://learn.microsoft.com/en-us/azure/cognitive-services/content-moderator/text-moderation-api#classification Content Moderator's machine-assisted text classification feature supports English only, and helps detect potentially undesired content. The flagged content may be assessed as inappropriate depending on context. It conveys the likelihood of each category. The feature uses a trained model to identify possible abusive, derogatory or discriminatory language. This includes slang, abbreviated words, offensive, and intentionally misspelled words. Category1 refers to potential presence of language that may be considered sexually explicit or adult in certain situations.
Source: Adapted from community discussion — zellck
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. Select and Place:
This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.
Answer: See figure below
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
Source: Adapted from community discussion — Nebary
You are building a chatbot for a travel agent. The bot will ask users for a destination and must repeat the question until a valid input is received, or the user closes the conversation. Which type of dialog should you use?
Answer: A
A is the answer. https://learn.microsoft.com/en-us/azure/bot-service/bot-builder-concept-dialog?view=azure-bot-service-4.0#dialog-types The dialogs library provides a few types of dialogs to make your bot's conversations easier to manage. - prompt dialogs Ask the user for input and return the result. A prompt will repeat until it gets valid input or it's canceled. They're designed to work with waterfall dialogs.
Source: Adapted from community discussion — zellck
You are building a chatbot. You need to configure the chatbot to query a knowledge base. Which dialog class should you use?
Answer: A
A is the answer. https://learn.microsoft.com/en-us/azure/bot-service/bot-builder-concept-dialog?view=azure-bot-service-4.0#dialog-types The dialogs library provides a few types of dialogs to make your bot's conversations easier to manage. - QnA Maker dialog Automates access to a QnA Maker knowledge base. This dialog is designed to also work as an action within Composer.
Source: Adapted from community discussion — zellck
Keyboard:J Kmove between questionsA–Dselect an answerRshow or hide the answer← →change page
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