Microsoft AI-900 Online Practice Questions and Exam Preparation

Microsoft AI-900 Online Questions & Answers

• Question 131:

  Your company is exploring the use of voice recognition technologies in its smart home devices. The company wants to identify any barriers that might unintentionally leave out specific user groups.

  This an example of which Microsoft guiding principle for responsible AI?

  A. accountability
  B. fairness
  C. inclusiveness
  D. privacy and security
  C. inclusiveness

  ---

  Explanation

  References:

  https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

  AI systems should empower everyone and engage people. AI should bring benefits to all parts of society, regardless of physical ability, gender, sexual orientation, ethnicity, or other factors. (https://docs.microsoft.com/en-us/learn/modules/get-started-ai-fundamentals/7-understand-responsible-ai)

• Question 132:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

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  According to the Microsoft Azure AI Fundamentals (AI-900) official study materials and Microsoft Learn documentation on GitHub Copilot, the GitHub Copilot extension for Microsoft Visual Studio Code (VS Code) is powered by the OpenAI Codex model, a specialized descendant of the GPT (Generative Pre-trained Transformer) family of models. The OpenAI Codex model is specifically fine-tuned for programming tasks-it understands and generates code in multiple programming languages such as Python, JavaScript, C#, and more. GitHub Copilot functions as an AI-powered coding assistant that suggests complete lines or blocks of code, helps write comments, and can even generate functions based

  on natural language prompts entered by the developer. When a user types a comment like "// sort a list of numbers in ascending order," Copilot uses the Codex model to understand the intent and generate an appropriate code implementation. The integration with Visual Studio Code allows developers to work efficiently without needing to switch between documentation and their coding environment. GitHub Copilot leverages context-aware suggestions, meaning it understands the surrounding code, function definitions, and variable names to provide relevant completions.

  The other options are incorrect because: GitHub source control manages code repositories but doesn't use AI models. IntelliSense is a built-in VS Code feature for code completion but doesn't rely on OpenAI models. Microsoft 365 Copilot uses large language models (like GPT-4) for productivity tools such as Word, Excel, and Outlook-not for code generation. Therefore, the correct choice that uses the OpenAI Codex model in Visual Studio Code is GitHub Copilot, aligning with Microsoft's AI-900 learning objectives under "Identify common use cases for Azure OpenAI and GitHub Copilot."

• Question 133:

  Which two scenarios are examples of a natural language processing workload? Each correct answer presents a complete solution.

  NOTE; Each correct selection is worth one point.

  A. assembly line machinery that autonomously inserts headlamps into cars
  B. a smart device in the home that responds to questions such as, "What will the weather be like today?
  C. monitoring the temperature of machinery to turn on a fan when the temperature reaches a specific threshold
  D. a website that uses a knowledge base to interactively respond to users' questions
  B. a smart device in the home that responds to questions such as, "What will the weather be like today?
  D. a website that uses a knowledge base to interactively respond to users' questions

• Question 134:

  You need to identify street names based on street signs in photographs.

  Which type of computer vision should you use?

  A. object detection
  B. optical character recognition (OCR)
  C. image classification
  D. facial recognition
  B. optical character recognition (OCR)

• Question 135:

  DRAG DROP

  Match the Azure Al service to the appropriate actions.

  To answer, drag the appropriate service from the column on the left to its action on the right Each service may be used once, more than once, or not at all.

  NOTE: Each correct match is worth one point.

  Select and Place:

  

  

• Question 136:

  A chatbot application must understand user intents such as booking flights, checking weather, or requesting support.

  Which Azure AI capability should be used?

  A. Conversational language understanding
  B. Optical character recognition
  C. Image classification
  D. Face detection
  A. Conversational language understanding

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  Explanation

  Conversational language understanding identifies user intents and extracts relevant entities from natural language. This capability is essential for building chatbots that understand and respond to user requests.

• Question 137:

  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

  

  

• Question 138:

  Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?

  A. Form Recognizer
  B. Text Analytics
  C. Ink Recognizer
  D. Custom Vision
  A. Form Recognizer

  ---

  Explanation

  Accelerate your business processes by automating information extraction. Form Recognizer applies advanced machine learning to accurately extract text, key/value pairs, and tables from documents. With just a few samples, Form Recognizer tailors its understanding to your documents, both on-premises and in the cloud. Turn forms into usable data at a fraction of the time and cost, so you can focus more time acting on the information rather than compiling it.

  References:

  https://azure.microsoft.com/en-us/services/cognitive-services/form-recognizer/

• Question 139:

  You need to determine the location of cars in an image so that you can estimate the distance between the cars.

  Which type of computer vision should you use?

  A. optical character recognition (OCR)
  B. object detection
  C. image classification
  D. face detection
  B. object detection

  ---

  Explanation

  Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.

  The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like "indoor", which can't be localized with bounding boxes.

  References:

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

• Question 140:

  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.

  NOTE: Each correct match is worth one point.

  Select and Place:

  

  

  ---

  Box 1: Reliability and safety Reliability and safety: AI systems should perform reliably and safely.

  Box 2: Privacy and security Privacy and security: AI systems should be secure and respect privacy.

  Incorrect:

  Inclusiveness: AI systems should empower everyone and engage people.

  Fairness: AI systems should treat all people fairly.

  References:

  https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai