Microsoft AI-900 Online Practice Questions and Exam Preparation

Microsoft AI-900 Online Questions & Answers

• Question 221:

  You have 100 instructional videos that do NOT contain any audio. Each instructional video has a script.

  You need to generate a narration audio file for each video based on the script.

  Which type of workload should you use?

  A. language modeling
  B. speech recognition
  C. speech synthesis
  D. translation
  C. speech synthesis

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  Explanation

  Text to speech enables your applications, tools, or devices to convert text into humanlike synthesized speech. The text to speech capability is also known as speech synthesis. Use humanlike prebuilt neural voices out of the box, or create a custom neural voice that's unique to your product or brand.

  References:

  https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/text-to-speech

• Question 222:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

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  According to the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore fundamental principles of machine learning," a regression model is used when the goal is to predict a continuous numerical value based on historical data. In this question, the task is to predict the sale price of auctioned items, which is a numeric output that can take on a wide range of values (for example, $50.25, $199.99, etc.). This makes it a regression problem because the output is continuous rather than categorical. Regression models analyze the relationship between input features (such as item type, condition, age, bidding history, or demand) and a numerical target variable (the sale price). Common regression algorithms include linear regression, decision tree regression, and neural network regression. In Azure Machine Learning, these models are trained using labeled datasets containing known outcomes to learn patterns and make future predictions. Let's review the incorrect options:

  Classification: Used to predict discrete categories or labels, such as "sold" vs. "unsold" or "low," "medium," "high." It cannot output continuous numeric predictions.

  Clustering: An unsupervised technique used to group similar data points based on shared characteristics, not to predict specific numeric outcomes. Therefore, because predicting a sale price involves forecasting a continuous numerical value, the correct model type is Regression. This aligns with Microsoft's AI-900 teaching that regression is used for tasks such as: Predicting house prices Forecasting sales revenue Estimating car values or auction prices

• Question 223:

  What can be used to analyze scanned invoices and extract data, such as billing addresses and the total amount due?

  A. Azure Al Search
  B. Azure Al Document intelligence
  C. Azure Al Custom Vision
  D. Azure OpenAI
  B. Azure Al Document intelligence

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  Explanation

  The correct answer is B. Azure AI Document Intelligence (formerly Form Recognizer). This Azure service uses AI and OCR technologies to analyze and extract structured data from documents such as invoices, receipts, and purchase orders.

  It identifies key fields like billing address, invoice number, total amount due, and line items. The service supports prebuilt models for common document types and custom models for specialized layouts. Option review:

  A. Azure AI Search: Used for knowledge mining and semantic search, not document data extraction.

  B. Azure AI Document Intelligence - # Correct. Designed for form and invoice extraction.

  C. Azure AI Custom Vision: Used for image classification and object detection, not text extraction.

  D. Azure OpenAI: Generates or processes language but not structured document data. Therefore, Azure AI Document Intelligence is the right service to extract data from scanned invoices.

• Question 224:

  Your website has a chatbot to assist customers.

  You need to detect when a customer is upset based on what the customer types in the chatbot.

  Which type of AI workload should you use?

  A. anomaly detection
  B. semantic segmentation
  C. regression
  D. natural language processing
  D. natural language processing

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  Explanation

  Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.

  Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.

  References:

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

• Question 225:

  You need to build an app that will identify celebrities in images.

  Which service should you use?

  A. Azure OpenAI Service
  B. Azure Machine Learning
  C. conversational language understanding (CLU)
  D. Azure Al Vision
  D. Azure Al Vision

• Question 226:

  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.

  

  

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  Box 1: Yes

  Azure Cognitive Service for Language provides features including:

  * Language detection: This pre-configured feature evaluates text, and determines the language it was written in. It returns a language identifier and a score that indicates the strength of the analysis.

  Box 2: No

  Handwritten detection is part of OCR (Optical Character Recognition).

  Box 3: Yes

  Azure Cognitive Service for Language provides features including:

  *

  Named Entity Recognition (NER): This pre-configured feature identifies entities in text across several pre-defined categories.

  Note: Named entity recognition is a natural language processing technique that can automatically scan entire articles and pull out some fundamental entities in a text and classify them into predefined categories. Entities may be, Organizations, Quantities, Monetary values, Percentages, and more.

  People's names

  Company names

  Geographic locations (Both physical and political) Product names Dates and times Amounts of money Names of events

  References:

  https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/overview

• Question 227:

  DRAG DROP

  You need to scan the news for articles about your customers and alert employees when there is a negative article. Positive articles must be added to a press book.

  Which natural language processing tasks should you use to complete the process? To answer, drag the appropriate tasks to the correct locations. Each task 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.

  Select and Place:

  

  

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  Box 1: Entity recognition

  the Named Entity Recognition module in Machine Learning Studio (classic), to identify the names of things, such as people, companies, or locations in a column of text.

  Named entity recognition is an important area of research in machine learning and natural language processing (NLP), because it can be used to answer many real-world questions, such as: Which companies were mentioned in a news article?

  Does a tweet contain the name of a person? Does the tweet also provide his current location?

  Were specified products mentioned in complaints or reviews?

  Box 2: Sentiment Analysis

  The Text Analytics API's Sentiment Analysis feature provides two ways for detecting positive and negative sentiment. If you send a Sentiment Analysis request, the API will return sentiment labels (such as "negative", "neutral" and "positive") and confidence scores at the sentence and document-level.

  References:

  https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/named-entity-recognitionhttps://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis

• Question 228:

  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.

  

  

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  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.

  References:

  https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks

• Question 229:

  What should you implement to identify hateful responses returned by a generative Al solution?

  A. prompt engineering
  B. abuse monitoring
  C. content filtering
  D. fine-tuning
  D. fine-tuning

• Question 230:

  HOTSPOT

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

  

  

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  Box: object detection

  Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found in the image. For example, if an image contains a dog, cat and person, the Detect operation will list those objects 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 object in an image.

  References:

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