Bootcamp AI-901: Microsoft Azure AI Fundamentals Course

AI 901 Microsoft Azure AI Fundamentals Practice TestPass the Microsoft AI-901 Azure AI Fundamentals certification with a complete exam prep course, including 324 practice tests and exam-style questions covering AI workloads, responsible AI principles, generative AI, machine learning, and Microsoft Foundry.Prepare for the Microsoft AI-901: Azure AI Fundamentals Certification Exam with a comprehensive course designed to help you master Microsoft Azure AI concepts and successfully pass the AI-901 certification.Whether you are a technical beginner or an aspiring AI developer looking to validate your foundational AI skills, this course will help you learn core Microsoft AI services, generative AI and agents, responsible AI frameworks, basic Python syntax, and AI application building using Microsoft Foundry.The course is strictly aligned with the newly updated official Microsoft AI-901 exam syllabus, ensuring you are fully prepared for the 2026 certification exam.AI-901 Exam Domains CoveredThis course follows the official Azure AI Fundamentals certification AI-901 exam skills outline, ensuring complete coverage of the newly structured certification exam topics. The AI-901 exam measures your knowledge across two major domains:Identify AI concepts and responsibilities (40–45%)Implement AI solutions by using Microsoft Foundry (55–60%)Identify AI concepts and capabilities (40–45%)Describe principles of responsible AIDescribe considerations for fairness in an AI solutionDescribe considerations for reliability and safety in an AI solutionDescribe considerations for privacy and security in an AI solutionDescribe considerations for inclusiveness in an AI solutionDescribe considerations for transparency in an AI solutionDescribe considerations for accountability in an AI solutionIdentify AI model components and configurationsDescribe how generative AI models workIdentify an appropriate AI model, based on capabilitiesIdentify appropriate model deployment options and configuration parametersIdentify AI workloadsIdentify scenarios for common AI workloads, including generative and agentic AI, text analysis, speech, computer vision, and information extractionDescribe common text analysis techniques, including keyword extraction, entity detection, sentiment analysis, and summarizationIdentify features and capabilities of speech recognition and speech synthesisIdentify features and capabilities of computer vision and image-generation modelsIdentify techniques to extract information from text, images, audio, and videosImplement AI solutions by using Microsoft Foundry (55–60%)Implement generative AI apps and agents by using FoundryCreate effective system and user prompts for generative AI modelsDeploy a model and interact with it in the Foundry portalCreate a lightweight chat client application by using the Foundry SDKCreate and test a single-agent solution in the Foundry portalCreate a lightweight client application for an agentImplement AI solutions for text and speech by using FoundryBuild a lightweight application that includes text analysisRespond to spoken prompts by using a deployed multimodal modelBuild a lightweight application by using Azure Speech in Foundry ToolsImplement AI solutions with computer vision and image-generation capabilities by using FoundryInterpret visual input in prompts by using a deployed multimodal modelCreate new visual outputs by using generative modelsBuild a lightweight application that includes vision capabilitiesImplement AI solutions for information extraction by using FoundryExtract information from documents and forms by using Azure Content Understanding in Foundry ToolsExtract information from images by using Content UnderstandingExtract information from audio and video by using Content UnderstandingBuild a lightweight application with information extraction capabilities by using Content UnderstandingHappy LearningTeam Codaming