Microsoft AI-900 : Microsoft Azure AI Fundamentals

  • Exam Code: AI-900
  • Exam Name: Microsoft Azure AI Fundamentals
  • Updated: Aug 10, 2026   Q&As: 336 Questions and Answers

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Describe NLP Workloads Features on Azure (15-20%)

This domain contains the following details that you need to learn about:

  • Identify Azure services & tools for Natural Language Processing Workloads – This topic is created to equip you with the ability to identify various capabilities, such as Speech service, Text Analytics service, Translator Text service, and Language Understanding service.
  • Identify the features of basic NLP (Natural Language Processing) Workload Scenarios – The individuals should be able to identify various uses and features of various components, for example, keyphrase extraction, sentiment analysis, entity recognition, translation, language modeling, and speech recognition & synthesis.

Certification Path of Microsoft AI-900 Exam

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Exam AI-900: Microsoft Azure AI Fundamentals

Candidates for this exam should have foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services.

This exam is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.

This exam is intended for candidates with both technical and non-technical backgrounds. Data science and software engineering experience are not required; however, some general programming knowledge or experience would be beneficial.

Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them.

Part of the requirements for: Microsoft Certified: Azure AI Fundamentals

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Microsoft AI-900 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Describe Artificial Intelligence workloads and considerations: It identifies specifications of common AI workloads and guiding principles for responsible AI.
Topic 2
  • Describe features of computer vision workloads on Azure: This topic discusses identifying common types of computer vision solution, Azure tools and services for computer vision tasks.
Topic 3
  • Describe fundamental principles of machine learning on Azure: It describes core machine learning concepts and Azure Machine Learning capabilities. Moreover, the topic also delves into identifying common machine-learning techniques.
Topic 4
  • Describe features of Natural Language Processing (NLP) workloads on Azure: In this topic, questions about common NLP Workload Scenarios features, Azure tools, and services for NLP workloads appear.
Topic 5
  • Describe features of generative AI workloads on Azure: Features of generative AI solutions and capabilities of Azure OpenAI Service are discussed in this topic.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

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