AI-901 Preparation Details
Preparing for the AI-901 Microsoft Azure AI Fundamentals certification exam? Start here with a complete, objective-wise AI-901 study guide designed to help you pass faster.
This guide brings together official Microsoft documentation, key concepts, and curated resources for every AI-901 exam objective, making it ideal for both beginners and last-minute revision.
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AI-901 Azure AI Fundamentals Materials
| Udemy | Azure AI Fundamentals Exam Prep In One Day |
| Coursera | Azure AI Fundamentals Exam Prep Specialization |
| Whizlabs | Microsoft Azure AI Fundamentals |
Identify AI concepts and capabilities (40–45%)
Describe principles of responsible AI
Describe considerations for fairness in an AI solution
What is Responsible AI – Azure Machine Learning
Adopt responsible and trusted AI principles – Cloud Adoption Framework
Describe considerations for reliability and safety in an AI solution
Embrace Responsible AI Principles and Practices – Training
Responsible AI in Azure Workloads – Azure Well-Architected Framework
Describe considerations for privacy and security in an AI solution
What is Responsible AI – Azure Machine Learning
Artificial Intelligence overview – Microsoft Service Assurance
Describe considerations for inclusiveness in an AI solution
Adopt responsible and trusted AI principles – Cloud Adoption Framework
Apply responsible AI principles in learning environments – Training
Describe considerations for transparency in an AI solution
Responsible AI in Azure Workloads – Azure Well-Architected Framework
Embrace Responsible AI Principles and Practices – Training
Describe considerations for accountability in an AI solution
What is Responsible AI – Azure Machine Learning
Identify guiding principles for responsible AI – Training
Identify AI model components and configurations
Describe how generative AI models work
Microsoft Foundry Models overview
Introduction to generative AI and agents – Training
Identify an appropriate AI model, based on capabilities
Foundry Models sold directly by Azure – Microsoft Foundry
Foundry Models from partners and community – Microsoft Foundry
Identify appropriate model deployment options and configuration parameters
Deployment overview for Azure AI Foundry Models
Understanding deployment types in Microsoft Foundry Models
Identify AI workloads
Identify scenarios for common AI workloads, including generative and agentic AI, text analysis, speech, computer vision, and information extraction
AI Architecture Design – Azure Architecture Center
Describe common text analysis techniques, including keyword extraction, entity detection, sentiment analysis, and summarization
What is Azure Language in Foundry Tools
What is sentiment analysis and opinion mining in Azure Language service?
What is summarization? – Foundry Tools
Identify features and capabilities of speech recognition and speech synthesis
What Is Azure Speech? – Foundry Tools
Text to speech overview – Speech service – Foundry Tools
Choose an Azure Speech Recognition and Generation Technology – Azure Architecture Center
Identify features and capabilities of computer vision and image-generation models
What is Azure Vision in Foundry Tools?
What is Image Analysis? – Foundry Tools
Get started with computer vision in Azure – Training
Identify techniques to extract information from text, images, audio, and videos
What is Azure Content Understanding in Foundry Tools?
Azure Content Understanding in Foundry Tools FAQ
Use AI Enrichment With Image and Text Processing – Azure Architecture Center
Implement AI solutions by using Microsoft Foundry (55–60%)
Implement generative AI apps and agents by using Foundry
Create effective system and user prompts for generative AI models
Prompt engineering techniques – Microsoft Foundry
System message design for Azure OpenAI – Microsoft Foundry
Image prompt engineering techniques – Microsoft Foundry
Deploy a model and interact with it in the Foundry portal
Microsoft Foundry Models overview
Create a lightweight chat client application by using the Foundry SDK
Basic Microsoft Foundry Chat Reference Architecture – Azure Architecture Center
Create and test a single-agent solution in the Foundry portal
Quickstart: Create a new Foundry Agent Service project
Quickstart: Deploy your first hosted agent – Microsoft Foundry
Create a lightweight client application for an agent
Baseline Microsoft Foundry Chat Reference Architecture – Azure Architecture Center
Implement AI solutions for text and speech by using Foundry
Build a lightweight application that includes text analysis
What is Azure Language in Foundry Tools
Develop natural language solutions in Azure – Training
Respond to spoken prompts by using a deployed multimodal model
Use the LLM-speech API – Speech service – Foundry Tools
Voice Live API Overview – Foundry Tools
Build a lightweight application by using Azure Speech in Foundry Tools
Create speech-enabled apps with Microsoft Foundry – Training
Speech to text quickstart – Foundry Tools
Text to speech quickstart – Speech service – Foundry Tools
Implement AI solutions with computer vision and image-generation capabilities by using Foundry
Interpret visual input in prompts by using a deployed multimodal model
How to use vision-enabled chat models – Microsoft Foundry
Develop computer vision solutions with Microsoft Foundry – Training
Create new visual outputs by using generative models
How to Use Image Generation Models from OpenAI – Microsoft Foundry
Video generation with Sora 2 – Microsoft Foundry
Build a lightweight application that includes vision capabilities
Get started with computer vision in Azure – Training
What is Azure Vision in Foundry Tools?
Implement AI solutions for information extraction by using Foundry
Extract information from documents and forms by using Azure Content Understanding in Foundry Tools
What is Azure Content Understanding in Foundry Tools?
Quickstart: Azure Content Understanding in Foundry Tools – REST API
Extract information from images by using Content Understanding
Azure Content Understanding in Foundry Tools standard and pro modes
What is Azure Content Understanding in Foundry Tools?
Extract information from audio and video by using Content Understanding
Azure Content Understanding in Foundry Tools video overview
Transparency Note and use cases for Content Understanding – Foundry Tools
Build a lightweight application with information extraction capabilities by using Content Understanding
Quickstart: Azure Content Understanding in Foundry Tools – REST API
Develop information extraction solutions with Microsoft Foundry – Training
This brings us to the end of the AI-901 Microsoft Azure AI Fundamentals Study Guide.
What do you think? Let me know in the comments section if I have missed out on anything. Also, I love to hear from you about how your preparation is going on!
In case you are preparing for other Azure certification exams, check out the Azure certification study guides for those exams.
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