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Microsoft Azure AI Fundamentals AI-900 Practice Test

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

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Full explanations included
Domain score breakdown
Real exam: 60 min
Pass mark: 700/1000

This exam was retired by the vendor on June 30, 2026.

AI-900 can no longer be scheduled. The practice material below remains available for reference and for learners studying the underlying skills. See Microsoft's current AI certifications

Sample questions with explanations

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Q1Describe features of computer vision workloads on Azureeasy
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Which Azure AI service can analyze an image and return a description of its contents in natural language?

AAzure AI Language
Azure AI Vision (Computer Vision)Correct
CAzure AI Speech
DAzure Bot Service

Azure AI Vision (Computer Vision) includes an image analysis API that can generate a human-readable description of an image's contents. This feature uses deep learning models to identify objects, actions, and scenes, then produces a natural language caption describing the image. …Read full explanation

Q2Describe Artificial Intelligence workloads and considerationshard
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A bank deploys an AI system that uses a complex deep learning model to approve or reject loan applications. When a loan is rejected, customers demand to know the specific reasons. The bank wants to ensure the AI system operates in a way that allows them to explain its decisions. Which Microsoft responsible AI principle is most directly relevant to this requirement?

AReliability and safety
TransparencyCorrect
CPrivacy and security
DFairness

The bank's requirement to explain why a loan was rejected directly aligns with the transparency principle, which mandates that AI systems be understandable and that their decisions can be communicated to users. In this scenario, the complex deep learning model must be interpretab…Read full explanation

Q3Describe Artificial Intelligence workloads and considerationseasy
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What is the 'accountability' principle in Microsoft's responsible AI framework?

AAI systems should automatically fix their own errors
Humans should maintain responsibility and oversight over AI systems and their impactsCorrect
CAI systems should log all user interactions for auditing
DAll AI code should be open-source for public review

The 'accountability' principle in Microsoft's responsible AI framework means that humans are ultimately responsible for the design, deployment, and outcomes of AI systems. This principle ensures that AI systems are not autonomous decision-makers without human oversight; instead, …Read full explanation

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