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JITA Learning · Certification

AI-901 · Microsoft Azure AI Fundamentals

Learn what each publication is designed to do, how the two guides work together, and choose the guide that matches your next step.

AI-901 study guide and exam preparation resources

Preparing for Microsoft Azure AI Fundamentals (AI-901)? JITA Learning provides a complementary Field Guide and Exam Preparation Guide designed to build practical understanding first, then test decision-making through certification-focused scenarios and changed-fact reasoning.

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Microsoft · Artificial Intelligence

AI-901 · Microsoft Azure AI Fundamentals

Foundation·Field Guide + Exam Preparation Guide
Choose your learning path

Each publication has a different job. Start with the guide that matches what you need now, or use them in sequence for the most complete JITA learning experience.

Field Guide

Build working judgment for Azure AI fundamentals.

This Field Guide develops a working mental model of Azure AI fundamentals. You will connect distinguish machine learning, generative AI, computer vision, language, speech, and information extraction workloads, recognize where Azure AI and Foundry capabilities fit common solution requirements, understand foundational model, prompt, agent, and application concepts, and apply responsible AI principles to business and technical scenarios. You are not just memorizing feature names; you are learning what owns the requirement, what can fail, and how to verify the outcome.

You’ll learn to distinguish:
  • machine learning workload vs generative AI workload
  • vision vs language or speech requirement
  • AI capability fit vs responsible-use constraint
Exam Preparation Guide

Prove your AI-901 judgment across Azure AI fundamentals under exam-style conditions.

This Exam Preparation Guide tests whether your understanding of Azure AI fundamentals survives realistic decision pressure. You will practice separating machine learning workload vs generative AI workload, vision vs language or speech requirement, and AI capability fit vs responsible-use constraint. Each scenario is designed to make you identify the governing fact, reject the nearest plausible alternative, and explain the evidence that keeps the correct answer correct.

You’ll learn to distinguish:
  • machine learning workload vs generative AI workload
  • vision vs language or speech requirement
  • AI capability fit vs responsible-use constraint
How the guides complement each other

Understand it first. Then prove you can apply it.

The Field Guide builds the understanding. Use it when you need the architecture, mechanics, dependencies, tradeoffs, failure paths, and verification logic behind the certification.

The Exam Preparation Guide tests the judgment. Use it when you need to practice under exam-style conditions, distinguish close answers, and understand why the correct answer survives changed facts.

Recommended sequence: Field Guide → Exam Preparation Guide → return to the Field Guide for targeted remediation where needed.