Microsoft AI-900 Online Practice Questions and Exam Preparation

Microsoft AI-900 Online Questions & Answers

• Question 201:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

  ---

  According to the Microsoft Azure AI Fundamentals (AI-900) official study materials and the Microsoft Learn module "Describe Azure Machine Learning and Automated ML," Azure Machine Learning designer (formerly known as Azure Machine Learning Studio) is a drag-and-drop, low-code/no-code environment that allows users to create, train, and evaluate machine learning models visually - without the need for extensive programming knowledge. The designer provides a visual interface, known as the canvas, where users can: Import and prepare data using modules for data transformation and cleaning. Split data into training and testing datasets. Select and configure algorithms (classification, regression, or clustering). Train and evaluate the model. Deploy the model as a web service directly from the designer. The official Microsoft Learn content emphasizes that "Azure Machine Learning designer enables users to build, test, and deploy models by adding and connecting prebuilt modules on a visual interface." This allows business analysts, data professionals, and beginners to experiment with machine learning workflows without writing code. By comparison: Automatically performing common data preparation tasks refers to Automated ML, not the designer. Automatically selecting an algorithm is also part of Automated ML, which optimizes models algorithmically. Using a code-first notebook experience applies to Azure Machine Learning notebooks, intended for data scientists familiar with Python and SDKs. Therefore, as per the AI-900 study guide and Microsoft Learn documentation, the verified and correct answer is: # Adding and connecting modules on a visual canvas, which accurately describes how Azure Machine Learning designer operates.

• Question 202:

  You are developing a chatbot solution in Azure.

  Which service should you use to determine a user's intent?

  A. Translator Text
  B. QnA Maker
  C. Speech
  D. Language Understanding (LUIS)
  D. Language Understanding (LUIS)

  ---

  Explanation

  Language Understanding (LUIS) is a cloud-based API service that applies custom machine-learning intelligence to a user's conversational, natural language text to predict overall meaning, and pull out relevant, detailed information.

  Design your LUIS model with categories of user intentions called intents. Each intent needs examples of user utterances. Each utterance can provide data that needs to be extracted with machine-learning entities.

  References:

  https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis

• Question 203:

  Which AI service can you use to extract intent from a user input such as "Call me back later"?

  A. Azure Cognitive Search
  B. Translator
  C. Language
  D. Speech
  D. Speech

  ---

  Explanation

  The Cognitive Services Speech SDK provides two ways to recognize intents. An intent is something the user wants to do: book a flight, check the weather, or make a call. Using intent recognition, your applications, tools, and devices can determine what the user wants to initiate or do based on options you define in the Intent Recognizer or Conversational Language Understanding (CLU) model.

  1. Pattern matching

  The Speech SDK provides an embedded pattern matcher that you can use to recognize intents in a very strict way. This is useful for when you need a quick offline solution. This works especially well when the user is going to be trained in some way or can be expected to use specific phrases to trigger intents.

  2. Conversational Language Understanding

  Conversational language understanding (CLU) enables users to build custom natural language understanding models to predict the overall intention of an incoming utterance and extract important information from it.

  Both a Speech resource and Language resource are required to use CLU with the Speech SDK. The Speech resource is used to transcribe the user's speech into text, and the Language resource is used to recognize the intent of the utterance.

  References:

  https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/intent-recognition

• Question 204:

  You are building a voice-enabled application that converts spoken language into text.

  Which service should you use?

  A. Text Analytics
  B. Speech-to-text
  C. Translator
  D. Language Understanding
  B. Speech-to-text

  ---

  Explanation

  Speech-to-text converts spoken audio into written text and is part of the Azure Speech service.

• Question 205:

  What can be used to complete a paragraph based on a sentence provided by a user?

  A. Azure Al Language
  B. Azure OpenAI
  C. Azure Machine Learning
  D. Azure Al Vision
  B. Azure OpenAI

• Question 206:

  DRAG DROP

  You plan to use Azure Cognitive Services to develop a voice controlled personal assistant app.

  Match the Azure Cognitive Services to the appropriate tasks.

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

  NOTE: Each correct selection is worth one point.

  Select and Place:

  

  

• Question 207:

  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.

  

  

  ---

  Box 1: Yes

  Azure Machine Learning designer lets you visually connect datasets and modules on an interactive canvas to create machine learning models.

  Box 2: Yes

  With the designer you can connect the modules to create a pipeline draft.

  As you edit a pipeline in the designer, your progress is saved as a pipeline draft.

  Box 3: No

  References:

  https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer

• Question 208:

  DRAG DROP

  Match the machine learning models to the appropriate deceptions.

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

  NOTE: Each correct match is worth one point.

  Select and Place:

  

  

• Question 209:

  You are designing an AI system that must perform consistently under varying conditions and minimize failures.

  Which responsible AI principle is being addressed?

  A. fairness
  B. transparency
  C. reliability and safety
  D. inclusiveness
  C. reliability and safety

  ---

  Explanation

  Reliability and safety ensure that AI systems perform as expected under different conditions and handle errors appropriately.

• Question 210:

  You need to convert handwritten notes into digital text.

  Which type of computer vision should you use?

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

  ---

  Explanation

  Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text.

  References:

  https://en.wikipedia.org/wiki/Optical_character_recognition