AI-900 practice questions 51–60

1. Question 51 · 236 in bank

   HOTSPOT - 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:

   

   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.

   Show the answer figure

   Answer: See figure below

   Explanation

   It is a duplicate question, only the previous one had answers Y/Y/N. Please be consistent with your answers, if you want money for subscription (and also be taken seriously as a website).

   Source: Adapted from community discussion — ArchMelody

   References

   • Microsoft Learn

   

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2. Question 52 · 236 in bank

   HOTSPOT - 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:

   

   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.

   Show the answer figure

   Answer: See figure below

   Explanation

   Box 1: No - Build conversational experiences with Power Virtual Agents and Azure Bot Service Azure Bot Service provides an integrated development environment for bot building. Its integration with Power Virtual Agents, a fully hosted low-code platform, enables developers of all technical abilities build conversational AI botsג€"no code needed. Box 2: Yes - Box 3: Yes - You can configure your bot to communicate with people via Microsoft Teams. Reference: https://azure.microsoft.com/en-us/services/bot-services/#overview https://docs.microsoft.com/en-us/azure/bot-service/channel-connect-teams

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn
   • Microsoft Learn

   

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3. Question 53 · 236 in bank

   HOTSPOT - Select the answer that correctly completes the sentence. Hot Area:

   

   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.

   Show the answer figure

   Answer: See figure below

   Explanation

   Azure's Computer Vision service gives you access to advanced algorithms that process images and return information based on the visual features you're interested in. * Optical Character Recognition (OCR) * Spatial Analysis * Image Analysis The Image Analysis service extracts many visual features from images, such as objects, faces, adult content, and auto-generated text descriptions. Follow the Image Analysis quickstart to get started. Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn

   

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4. Question 54 · 236 in bank

   HOTSPOT - To complete the sentence, select the appropriate option in the answer area. Hot Area:

   

   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.

   Show the answer figure

   Answer: See figure below

   Explanation

   Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn
   • Microsoft Learn

   

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5. Question 55 · 236 in bank

   You have an Azure Machine Learning pipeline that contains a Split Data module. The Split Data module outputs to a Train Model module and a Score Model module. What is the function of the Split Data module?

   • Ascaling numeric variables so that they are within a consistent numeric range
   • Bcreating training and validation datasets
   • Cdiverting records that have missing data
   • Dselecting columns that must be included in the model

   Show answer

   Answer: B

   Explanation

   B is the answer. https://learn.microsoft.com/en-us/azure/machine-learning/component-reference/split-data?view=azureml-api-2 Use the Split Data component to divide a dataset into two distinct sets. This component is useful when you need to separate data into training and testing sets. You can also customize the way that data is divided. Some options support randomization of data. Others are tailored for a certain data type or model type.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn

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6. Question 56 · 236 in bank

   Which statement is an example of a Microsoft responsible AI principle?

   • AAI systems must use only publicly available data
   • BAI systems must be transparent and inclusive
   • CAI systems must keep personal details public
   • DAI systems must protect the interests of the company

   Show answer

   Answer: B

   References

   • Microsoft Learn

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7. Question 57 · 236 in bank

   DRAG DROP - Match the types of natural language processing workloads to the appropriate scenarios. To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all. NOTE: Each correct match is worth one point. 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.

   Show the answer figure

   Answer: See figure below

   Explanation

   1. Entity recognition 2. Sentiment analysis 3. Translation https://learn.microsoft.com/en-us/azure/cognitive-services/language-service/named-entity-recognition/overview Named Entity Recognition (NER) is one of the features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The NER feature can identify and categorize entities in unstructured text. For example: people, places, organizations, and quantities. https://learn.microsoft.com/en-us/azure/cognitive-services/language-service/sentiment-opinion-mining/overview Sentiment analysis and opinion mining are features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. These features help you find out what people think of your brand or topic by mining text for clues about positive or negative sentiment, and can associate them with specific aspects of the text.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

   

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8. Question 58 · 236 in bank

   Select 2

   You need to reduce the load on telephone operators by implementing a chatbot to answer simple questions with predefined answers. Which two AI services should you use to achieve the goal? Each correct answers presents part of the solution. NOTE: Each correct selection is worth one point.

   • AAzure Machine Learning
   • BAzure Bot Service
   • CLanguage Service
   • DTranslator

   Show answer

   Answer: BC

   Explanation

   BC is the answer. https://learn.microsoft.com/en-us/training/modules/build-faq-chatbot-qna-maker-azure-bot-service/2-get-started-knowledge-base You can easily create a user support bot solution on Microsoft Azure using a combination of two core services: - Language service. The Language service includes a custom question answering feature that enables you to create a knowledge base of question and answer pairs that can be queried using natural language input. - Azure Bot service. This service provides a framework for developing, publishing, and managing bots on Azure.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn

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9. Question 59 · 236 in bank

   DRAG DROP - Match the principles of responsible AI to the appropriate descriptions. To answer, drag the appropriate principle from the column on the left to its description on the right. Each principle 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.

   

   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.

   Show the answer figure

   Answer: See figure below

   Explanation

   1. Reliability and safety 2. Privacy and security https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai#reliability-and-safety AI systems need to be reliable and safe in order to be trusted. It's important for a system to perform as it was originally designed and for it to respond safely to new situations. Its inherent resilience should resist intended or unintended manipulation. Rigorous testing and validation should be established for operating conditions to ensure that the system responds safely to edge cases, and A/B testing and champion/challenger methods should be integrated into the evaluation process.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn

   

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10. Question 60 · 236 in bank

    During the process of Machine Learning, when should you review evaluation metrics.

    • ABefore you train a model.
    • BAfter you clean the data.
    • CBefore you choose the type of model.
    • DAfter you test a model on the validation data.

    Show answer

    Answer: D

    Explanation

    D is the answer. https://learn.microsoft.com/en-us/training/modules/use-automated-machine-learning/5-machine-learning-steps You can think of the steps in a machine learning process as: - Prepare data: Identify the features and label in a dataset. Pre-process, or clean and transform, the data as needed. - Train model: Split the data into two groups, a training and a validation set. Train a machine learning model using the training data set. Test the machine learning model for performance using the validation data set. - Evaluate performance: Compare how close the model's predictions are to the known labels. - Deploy a predictive service: After you train a machine learning model, you can deploy the model as an application on a server or device so that others can use it.

    Source: Adapted from community discussion — zellck

    References

    • Microsoft Learn

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Keyboard:J Kmove between questionsA–Dselect an answerRshow or hide the answer← →change page

AI-900 practice, question 51. 236 questions available.