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AI-900 & AI-901-Microsoft Azure AI Fundamental Certification
Rating: 4.6 out of 5(7,515 ratings)
38,196 students

What you'll learn

  • Prepare for both the AI-900 exam and the new AI-901 beta exam — covering all official Microsoft exam objectives for both certifications.
  • Understand core AI concepts including machine learning, deep learning, NLP, computer vision, generative AI, and agentic AI.
  • Learn the principles of Responsible AI — fairness, transparency, accountability, privacy, inclusiveness, reliability, and safety.
  • Deploy and interact with AI models using the Microsoft Foundry portal, including generative AI apps and single-agent solutions.
  • Build lightweight client applications using the Foundry SDK and extract information from documents, images, audio, and video using Azure Content Understanding.

Course content

10 sections • 173 lectures • 11h 13m total length

  • IMPORTANT - How the course has been structured6:03
  • Slides download0:08
  • What This Section Covers — And Why It Matters2:10
  • Generative AI - The Big Picture2:34

    A wide-angle view of what generative AI actually is and why it represents such a significant shift in how software is built.

  • Inside the LLM - From Prompt to Response7:18

    A look under the hood of large language models — what they are, how they're trained, and what actually happens between the moment you send a prompt and the moment you receive a response.

  • AI Models Landscape Anthropic and OpenAI7:31

    Let's have an overview of the various models in the market and focus our attention on the OpenAI models.

  • The Art of the Prompt Engineering - Better Conversations with AI5:41

    A practical guide to communicating with AI models in a way that gets consistently better results.

  • The Art of the Prompt Engineering - Better Conversations with AI - Resources0:20
  • Agentic AI - From Answering Questions to Getting Things Done4:22

    A conceptual shift from thinking about AI as a question-answering tool to understanding it as an autonomous actor that can plan, use tools, and complete multi-step tasks.

  • Identifying AI Workloads - Text3:27

    A focused look at the wide range of tasks AI models can perform with text

  • Identifying AI Workloads - Speech1:39

    An exploration of where AI adds value in audio and spoken language scenarios.

  • Identifying AI Workloads - Computer Vision2:14

    A survey of AI use cases that involve images and video, including object detection, image classification, optical character recognition, and visual inspection.

  • Identifying AI Workloads - Information Extraction2:30

    A chapter focused on one of the most practically valuable AI applications — pulling structured, usable information out of unstructured content like documents, forms, and reports.

  • Fairness - Building AI That Treats Everyone Equally6:08

    An honest examination of how bias enters AI systems and what it looks like when a model treats different groups of people unequally.

  • Reliability & Safety - AI That Works When It Matters4:11

    A chapter on what it means for an AI system to be reliable — not just accurate on average, but trustworthy across edge cases, unexpected inputs, and high-stakes situations.

  • Privacy & Security - Protecting People in an AI World4:59

    An exploration of the unique privacy and security challenges that come with AI systems

  • Inclusiveness - Designing AI for Every Human3:45

    A look at how AI systems can be designed to work well for people of all backgrounds, abilities, languages, and circumstances.

  • Transparency - Making AI Understandable5:42

    A chapter on the principle that AI systems should be explainable.

  • Accountability - Keeping Humans in Control5:11

    A discussion of who is responsible when an AI system gets something wrong.

  • From Theory to Practice What We're Going to Build1:26

    A bridge chapter that transitions from concepts to code.

  • Summary11:23
  • Section Quiz

Requirements

  • Azure AI services are cloud-based — some familiarity with Microsoft Azure or basic cloud concepts will be beneficial but is not required.
  • No prior development experience is needed for the AI-900 content. For AI-901 sections, basic Python coding syntax knowledge is recommended.
  • A basic understanding of data concepts such as structured/unstructured data and databases is useful when exploring AI models and services.

Description

Release v5.0 – May 2026 (AI-901 Beta Content Added)

The AI-900 exam will retire on June 30, 2026, and is being replaced by AI-901: Azure AI Fundamentals (Refreshed). Since AI-901 is currently in beta, this course now covers both exams so you can prepare for either path with confidence.

What's new in AI-901?

AI-901 is a substantial redesign that pivots from individual Azure AI services to the unified Microsoft Foundry platform. The new exam emphasises implementing generative AI apps and agents, deploying models in the Foundry portal, building lightweight client applications with the Foundry SDK, and extracting information using Azure Content Understanding. Examinotion

The exam is structured around two core skill areas:

  • Identify AI Concepts and Responsibilities (40–45%) — covering responsible AI principles, AI model components and configurations, and AI workloads including generative and agentic AI, text analysis, speech, computer vision, and information extraction Microsoft Learn

  • Implement AI Solutions using Microsoft Foundry (55–60%) — covering generative AI apps and agents, text and speech solutions, computer vision and image generation, and information extraction using Azure Content Understanding in Foundry Tools

Release v4.0 - August2025

Artificial Intelligence is no longer the future—it’s the present, reshaping how industries operate and how we work, live, and interact. With tools like ChatGPT and Azure AI becoming part of everyday workflows, staying current with AI fundamentals is not just useful—it’s essential.

The entire course has been updated and refreshed. All chapters have been re-recorded. This has been done to ensure that all contents now reflect the most recent changes to the services on the Azure platform.

All course contents have also been aligned as per any changes to the course objectives.

Release v3.0 - January 2025

The entire course has been updated and refreshed. All chapters have been re-recorded. This has been done to ensure that all contents now reflect the most recent changes to the services on the Azure platform.

All course contents have also been aligned as per any changes to the course objectives.

Additional questions also added to the Practice Tests available at the end of the course.

Release v2.0 - July 2023

The entire course has been updated and refreshed. All chapters have been re-recorded. This has been done to ensure that all contents now reflect the most recent changes to the services on the Azure platform.

All course contents have also been aligned as per any changes to the course objectives.

Quiz questions have also been added to the end of each section.


This course is a preparation course for students who want to attempt the Exam AI-900: Microsoft Azure AI Fundamentals

This course has contents for the Exam AI-900

The objectives covered in this course are

  • Describe AI workloads and considerations (15-20%) - Here we will discuss the the basics on AI-based workloads.

  • Describe fundamental principles of machine learning on Azure (30-35%) - Here we will understand what is Machine Learning. We will also look at labs on how to work with the Machine Learning service.

  • Describe features of computer vision workloads on Azure (15-20%) - Here we will look at the different features of the Computer Vision service. We will also look at the Custom Vision service, the Face service and the Form Recognizer service.

  • Describe features of Natural Language Processing (NLP) workloads on Azure (15-20%) - Here we will look at services such the Text Analytics service, the Language Understanding Intelligence Service , the Speech service.

  • Describe features of conversational AI workloads on Azure (15-20%) - Here we will see the basics on the QnA Maker service and the Bot Framework.

There is also a number of labs available in this course. These labs focus on the different services available in Azure when it comes to Machine Learning and Artificial Intelligence.

Who this course is for:

  • Beginners with no AI or Azure background who want to earn the Microsoft Azure AI Fundamentals certification via the AI-900 or the new AI-901 exam.
  • IT professionals and cloud practitioners looking to add AI skills to their existing Azure or cloud computing experience.
  • Aspiring AI developers who want a foundational understanding of Microsoft Foundry, generative AI apps, and AI agents before moving on to the AI Engineer or Data Scientist certifications.

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