Microsoft AI-900 Online Practice Questions and Exam Preparation

Microsoft AI-900 Online Questions & Answers

• Question 151:

  You plan to use Azure Machine Learning Studio and automated machine learning (automated ML) to build and train a model

  What should you create first?

  A. a Jupyter notebook
  B. a Machine Learning workspace
  C. a registered dataset
  D. a Machine Learning designer pipeline
  B. a Machine Learning workspace

• Question 152:

  You have an Internet of Things (loT) device that monitors engine temperature.

  The device generates an alert if the engine temperature deviates from expected norms.

  Which type of Al workload does the device represent?

  A. natural language processing (NLP)
  B. computer vision
  C. anomaly detection
  D. knowledge mining
  C. anomaly detection

• Question 153:

  Which AI service should you use to create a bot from a frequently asked questions (FAQ) document?

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

• Question 154:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

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  Box: Regression

  You can create a regression model with Azure Machine Learning designer.

  Regression is a supervised machine learning technique used to predict numeric values.

  According to the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore fundamental principles of machine learning," regression is a type of supervised machine learning used to predict continuous numeric values. In this question, the goal is to predict how many vehicles will travel across a bridge on a given day. The predicted output (the number of vehicles) is a continuous value-meaning it can take on any numerical value depending on various factors like time, weather, or day of the week. This makes it a regression problem, as the model learns from historical numeric data to estimate a continuous outcome.

  How Regression Works: Regression models find patterns between input features (such as temperature, weekday/weekend, traffic trends) and a numerical output (number of vehicles). Common regression algorithms include linear regression, decision trees for regression, and neural network regression. In Azure Machine Learning, regression tasks are used for business scenarios such as: Predicting sales revenue for a future month. Estimating house prices based on property characteristics. Forecasting energy consumption or traffic flow, as in this case. Why not the other options?

  Classification: Used for predicting discrete categories (e.g., "spam" vs. "not spam"). It does not handle continuous numeric values.

  Clustering: An unsupervised learning technique used to group data points based on similarity without predefined labels (e.g., segmenting customers into groups). Therefore, the task of predicting the number of vehicles-a numeric, continuous value-is a regression problem.

  References:

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

• Question 155:

  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 156:

  A team wants a generative AI model to answer questions using company documents stored in a knowledge base.

  Which technique allows the model to retrieve and use external information?

  A. Retrieval-augmented generation
  B. Image tagging
  C. Speech synthesis
  D. Video indexing
  A. Retrieval-augmented generation

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  Explanation

  Retrieval-augmented generation combines information retrieval with generative models so the AI can access external documents and generate more accurate answers.

• Question 157:

  You need to make the written press releases of your company available in a range of languages.

  Which service should you use?

  A. Speech
  B. Language
  C. Translator
  D. Personalizer
  C. Translator

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  Explanation

  Translator, an AI service for real-time document and text translation.

  Translate text instantly or in batches across more than 100 languages, powered by the latest innovations in machine translation. Support a wide range of use cases, such as translation for call centers, multilingual conversational agents, or in-app communication.

  References:

  https://azure.microsoft.com/en-us/services/cognitive-services/translator/4

• Question 158:

  HOTSPOT

  Select the answer that correctly completes the sentence.

  

  

  ---

  "features." According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Describe fundamental principles of machine learning on Azure," in a machine learning model, the data used as inputs are known as features, while the data that represents the output or target prediction is known as the label. Features are measurable attributes or properties of the data used by a model to learn patterns and make predictions. They are also referred to as independent variables because they influence the result that the model tries to predict. For example, in a machine learning model that predicts house prices: Features might include square footage, location, and number of bedrooms, while.

  The label would be the house price (the value being predicted). In the context of Azure Machine Learning, during model training, features are passed into the algorithm as input variables (X-values), and the label is the corresponding output (Y-value). The model then learns the relationship between the features and the label. Let's review the incorrect options:

  Functions: These are mathematical operations or relationships used inside algorithms, not the input data itself.

  Labels: These are the outputs or results that the model predicts, not the inputs.

  Instances: These refer to individual data records or rows in the dataset, not the input fields themselves. Hence, in any supervised or unsupervised learning process, the input data (independent variables) are called features, and the model uses them to predict labels (dependent variables).

• Question 159:

  You have a dataset that contains the columns shown in the following table.

  

  You have a machine learning model that predicts the value of ColumnE based on the other numeric columns.

  Which type of model is this?

  A. analysis
  B. clustering
  C. regression
  C. regression

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  Explanation

  Regression is a supervised machine learning technique used to predict numeric values.

  References:

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

• Question 160:

  HOTSPOT

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

  

  

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  To perform real-time inferencing, you must deploy a pipeline as a real-time endpoint.

  Real-time endpoints must be deployed to an Azure Kubernetes Service cluster.

  a local web service.

  Azure Container Instances.

  Azure Kubernetes Service.

  Azure Machine Learning compute.

  References:

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