Microsoft AI-900 Online Practice Questions and Exam Preparation

Microsoft AI-900 Online Questions & Answers

• Question 121:

  You need to analyze images of vehicles on a highway and measure the distance between the vehicles.

  Which type of computer vision model should you use?

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

• Question 122:

  What should you use to identify similar faces in a set of images?

  A. Azure Al Vision
  B. Azure Al Custom Vision
  C. Azure Al Language
  D. Azure OpenAI Service
  A. Azure Al Vision

• Question 123:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

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  Box: natural language processing

  Question answering provides cloud-based Natural Language Processing (NLP) that allows you to create a natural conversational layer over your data. It is used to find appropriate answers from customer input or from a project.

  References:

  https://learn.microsoft.com/en-us/azure/cognitive-services/language-service/question-answering/overview

• Question 124:

  You have a natural language processing (NLP) model that was created by using data obtained without permission.

  Which Microsoft principle for responsible AI does this breach?

  A. reliability and safety
  B. privacy and security
  C. inclusiveness
  D. transparency
  B. privacy and security

• Question 125:

  You need to identify groups of rows with similar numeric values in a dataset.

  Which type of machine learning should you use?

  A. clustering
  B. regression
  C. classification
  A. clustering

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  Explanation

  Clustering is an unsupervised machine learning technique used to group similar entities based on their features. Learn how to create clustering models using Azure Machine Learning designer.

  Scenarios for clustering machine learning models Clustering machine learning models are used in many industries.

  A few scenarios are:

  1. Cluster customer attribute data into segments for marketing analysis.

  2. Cluster geographic coordinates into regions of high traffic in a city for a ride-share application.

  3. Cluster written feedback into topics to prioritize customer service changes.

  References:

  https://learn.microsoft.com/en-us/training/modules/create-clustering-model-azure-machine-learning-designer/2-clustering-scenarios

• Question 126:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

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  The correct completion of the sentence "_____ is an example of speech recognition." is A voice-activated security key system. According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Describe features of common AI workloads", speech recognition refers to the ability of a system or application to convert spoken language into text or actionable commands. It allows computers to interpret and respond to human speech inputs, bridging human-computer interaction through natural language. Microsoft Learn clearly explains that speech recognition is used in applications such as voice assistants, dictation software, and voice-activated security systems, where the spoken input from a user is captured, analyzed, and translated into commands or text. For example, when a user says "Unlock door" or "Open session," the speech recognition system interprets that sound input, converts it into text or a command, and then performs the appropriate action. This is a direct implementation of speech-to-text processing combined with command execution logic. Let's analyze the other options: Creating an audio commentary for a video recording is related to speech synthesis (text-to-speech), not recognition. Creating captions for a video recording involves speech-to-text transcription, which is a subset of speech recognition, but the question emphasizes a system that responds to voice commands, making the first option more accurate. Identifying key phrases in a video transcript involves natural language processing (NLP) techniques rather than speech recognition. Therefore, the voice-activated security key system best represents the use of speech recognition technology because it interprets spoken commands and takes a corresponding action based on recognized speech patterns. This aligns directly with the AI-900 learning objectives where speech recognition is defined as a process that enables applications to interpret and respond to human voice input.

• Question 127:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

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  The correct answer is Document Intelligence. According to the Microsoft Azure AI Fundamentals (AI-900) study materials and Microsoft Learn documentation, the Azure AI Document Intelligence service (formerly known as Form Recognizer) is specifically designed to extract structured data from documents, including scanned invoices, receipts, forms, and business cards. This service combines optical character recognition (OCR) with machine learning to analyze both the layout and semantic meaning of document content. When processing scanned invoices, Document Intelligence identifies and extracts fields such as invoice numbers, dates, totals, taxes, vendor names, and line-item details. The extracted information can then be automatically imported into business systems like accounting software or databases, eliminating manual data entry and improving operational efficiency. Here's why the other options are incorrect:

  Generative AI: Focuses on creating new content such as text, images, or code (for example, using GPT-4 or DALL- E). It is not used for structured data extraction.

  Natural Language Processing (NLP): Deals with understanding and generating human language from text-based input, not document scanning or layout interpretation. The Document Intelligence workload excels at handling semi-structured documents where the location and format of data vary between samples. Microsoft's prebuilt models-like Invoice, Receipt, Identity Document, and Contract-simplify extraction without requiring custom training. In summary, if the task involves extracting data from scanned invoices, the appropriate Azure AI service is Azure AI Document Intelligence, which uses AI-powered document understanding to convert unstructured document images into structured, usable data.

• Question 128:

  Which two actions are performed during the data ingestion and data preparation stage of an Azure Machine Learning process? Each correct answer presents part of the solution.

  NOTE: Each correct selection is worth one point.

  A. Calculate the accuracy of the model.
  B. Score test data by using the model.
  C. Combine multiple datasets.
  D. Use the model for real-time predictions.
  E. Remove records that have missing values.
  C. Combine multiple datasets.
  E. Remove records that have missing values.

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  Explanation

  References:

  https://docs.microsoft.com/en-us/azure/machine-learning/concept-data-ingestionhttps://docs.microsoft.com/en-us/azure/architecture/data-science-process/prepare-data

• Question 129:

  You are developing a solution that predicts house prices based on historical data.

  Which type of machine learning should you use?

  A. classification
  B. clustering
  C. regression
  D. anomaly detection
  C. regression

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  Explanation

  Regression is used to predict numeric values, such as prices. It models the relationship between input features and a continuous output variable.

• Question 130:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

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  The correct answer is Azure AI Custom Vision. According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and the Microsoft Learn module "Explore computer vision in Azure", the Azure AI Custom Vision service is specifically designed to allow users to train, test, and deploy custom image classification and object detection models using their own images. The Azure AI Custom Vision service extends the capabilities of Azure's general-purpose Computer Vision API by enabling organizations to upload their own labeled datasets, define custom tags (labels), and train models that are optimized for their specific use cases. This makes it ideal for object detection scenarios-such as detecting equipment in a manufacturing line, identifying products on store shelves, or recognizing medical images-where general-purpose models may not suffice. By contrast, the Azure AI Computer Vision service provides pre-built models for tasks such as image description, tagging, face detection, and OCR (optical character recognition). It does not allow users to train their own models with custom data. Similarly, Azure AI Document Intelligence is used for extracting structured information from documents (forms, receipts, invoices), and Azure Video Analyzer for Media focuses on analyzing video content for insights and metadata extraction. The AI-900 study guide emphasizes that the Custom Vision service supports two key model types: Image Classification - categorizing entire images based on predefined tags. Object Detection - identifying and locating multiple objects within an image by drawing bounding boxes. Therefore, when the question specifies "train an object detection model by using your own images," the correct Azure service is Azure AI Custom Vision, as it provides the necessary tools for training, evaluating, and deploying custom computer vision models tailored to a user's dataset. Hence, the verified correct answer is: Azure AI Custom Vision.