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Microsoft Azure AI Fundamentals AI-900 Practice Test

1,020 questions with instant explanations, domain breakdown, and wrong-answer analysis. Built for the real exam.

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Domain score breakdown
Real exam: 60 min
Pass mark: 700%

Sample questions with explanations

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Q1Describe Artificial Intelligence workloads and considerationseasy
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A bank is developing an AI system to automatically approve personal loans. To ensure the system does not discriminate against any group of applicants, which Microsoft responsible AI principle should the bank primarily focus on?

AAccountability
BInclusiveness
FairnessCorrect
DReliability and Safety

Fairness is the correct principle because it directly addresses the need to prevent discrimination in AI systems, such as loan approval models. By focusing on fairness, the bank ensures that the model's predictions do not systematically disadvantage any group based on protected a…Read full explanation

Q2Describe fundamental principles of machine learning on Azuremedium
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A data scientist wants to train a machine learning model to predict the exact market price of a house based on features such as square footage, number of bedrooms, and location. Which type of machine learning task should be used?

AClassification
RegressionCorrect
CClustering
DAnomaly Detection

Predicting the exact market price of a house is a regression task because the target variable (price) is a continuous numeric value. Regression algorithms, such as linear regression or decision tree regression, learn the relationship between input features (e.g., square footage, …Read full explanation

Q3Describe features of computer vision workloads on Azuremedium
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A transportation company wants to automatically identify whether an image contains a car, a truck, or a motorcycle. The system should output a single label for the entire image. Which computer vision capability in Azure should they use?

AObject detection
Image classificationCorrect
COptical Character Recognition (OCR)
DSemantic segmentation

Image classification assigns a single label to an entire image based on its dominant content. Since the requirement is to output one label (car, truck, or motorcycle) per image, this maps directly to Azure's Custom Vision image classification capability, which trains a model to c…Read full explanation

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