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Microsoft AI-300 Practice Test Questions Answers

Exam Code: AI-300 (Updated 187 Q&As with Explanation)
 Exam Name: Operationalizing Machine Learning and Generative AI Solutions
 Last Update: 16-Sep-2026
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Questions Include:

  • Single Choice: 90 Q&A's
  • Multiple Choice: 18 Q&A's
  • Hotspot: 47 Q&A's
  • Drag Drop: 32 Q&A's

    • AI-300 Overview

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    AI-300 Questions and Answers

    Question # 1

    A data science team trains a classification model that predicts loan approval outcomes.

    Before registering the model, the team must ensure the following:

    Predictions must not disproportionately impact protected groups.

    Prediction errors can be evaluated across different data segments.

    You need to assess whether the model meets Responsible AI expectations.

    Which two approaches should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point. Choose two.

    A.

    Analyze error rates across the global cohort.

    B.

    Measure endpoint latency under load.

    C.

    Validate inference schema compatibility.

    D.

    Evaluate feature importance for prediction transparency.

    E.

    Analyze error rates across defined demographic cohorts.

    Question # 2

    Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

    After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.

    You manage an Azure Machine Learning workspace. The Python script named script.py reads an argument named training_data.

    The training_data argument specifies the path to the training data in a file named dataset1.csv.

    You plan to run the script.py Python script as a command job that trains a machine learning model.

    You need to provide the command to pass the path for the dataset as a parameter value when you submit the script as a training job.

    Solution: python train.py --training_data training_data

    Does the solution meet the goal?

    A.

    Yes

    B.

    No

    Question # 3

    You create an Azure Machine Learning workspace and install the MLflow library.

    You need to log different types of data by using the MLflow library.

    Which method should you use? To answer, select the appropriate options in the answer area.

    NOTE: Each correct selection is worth one point.

    Question # 4

    You train and publish a machine teaming model.

    You need to run a pipeline that retrains the model based on a trigger from an external system.

    What should you configure?

    A.

    Azure Data Catalog

    B.

    Azure Batch

    C.

    Azure logic App

    Question # 5

    You create an Azure Machine Learning workspace and install the MLflow library.

    You need to tog different types of data by using the MLflow library.

    Which method should you use? To answer, select the appropriate options in the answer area.

    NOTE: Each correct selection is worth one point.

    Free AI-300 Microsoft Exam Questions 6 to 25
    Free AI-300 Microsoft Exam Questions 26 to 39

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