Microsoft Azure AI Fundamentals (AI-900)
Unlimited AI-900 practice exam retakes, each drawn fresh from a question pool weighted by the official exam domains — covering AI workloads & considerations, machine learning on Azure, computer vision, natural language processing, and generative AI, aligned to the official AI-900 study guide.
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60-minute timer, flag for review and a review screen before you submit — just like test day.
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See the correct answer, the exam domain and a full explanation after every question.
What you get
- A 195-question pool — every attempt draws 65 fresh questions weighted by the official exam domains
- Unlimited retakes, lifetime access
- Score report by exam domain, with your score trend over time
- Answer review with explanations and reference links
- Original, blueprint-aligned questions — never exam dumps
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Exam domains
Every attempt draws questions in these official proportions. Open a domain to see the subtopics it covers.
Describe Artificial Intelligence workloads and considerations19%
- Identify computer vision workloads
- Identify natural language processing workloads
- Identify document processing workloads
- Identify features of generative AI workloads
- Responsible AI: fairness, reliability and safety, privacy and security
- Responsible AI: inclusiveness, transparency and accountability
Describe fundamental principles of machine learning on Azure19%
- Identify regression, classification and clustering machine learning scenarios
- Identify features of deep learning techniques and the Transformer architecture
- Identify features and labels in a dataset for machine learning
- Describe how training and validation datasets are used in machine learning
- Describe capabilities of automated machine learning
- Describe data and compute services for data science and machine learning
- Describe model management and deployment capabilities in Azure Machine Learning
Describe features of computer vision workloads on Azure19%
- Identify features of image classification solutions
- Identify features of object detection solutions
- Identify features of optical character recognition solutions
- Identify features of facial detection and facial analysis solutions
- Describe capabilities of the Azure AI Vision service
- Describe capabilities of the Azure AI Face detection service
Describe features of Natural Language Processing (NLP) workloads on Azure19%
- Identify features and uses for key phrase extraction and entity recognition
- Identify features and uses for sentiment analysis
- Identify features and uses for language modeling
- Identify features and uses for speech recognition and synthesis
- Identify features and uses for translation
- Describe capabilities of the Azure AI Language service
- Describe capabilities of the Azure AI Speech service
Describe features of generative AI workloads on Azure24%
- Identify features of generative AI models
- Identify common scenarios for generative AI
- Identify responsible AI considerations for generative AI
- Describe features and capabilities of Azure AI Foundry
- Describe features and capabilities of Azure OpenAI service
- Describe features and capabilities of Azure AI Foundry model catalog
References
- Official exam page:learn.microsoft.com
- Official study guide:learn.microsoft.com
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