ai900

Microsoft Azure AI Fundamentals (AI-900) Certification Prep

Short link: go.techtrainertim.com/ai900

Official preparation course for the Microsoft Azure AI Fundamentals (AI-900) certification exam. O’Reilly live training – 5 hours, 80% demos, 20% theory.

Exam Information

• Exam Code: AI-900
• Objectives Updated: May 2, 2025
• Official Page: Microsoft Learn AI-900
• Practice Assessment: Free official practice questions
• Exam Sandbox: aka.ms/examdemo

Course Flow (5 Segments)

Segment	Topic	Time	Exam Weight
S1	AI Fundamentals & Responsible AI	09:00 AM	15-20%
S2	Machine Learning	10:00 AM	15-20%
S3	Computer Vision	11:00 AM	15-20%
S4	Natural Language Processing	12:00 PM	15-20%
S5	Generative AI	01:00 PM	20-25% (highest)

For full objective details, see AI-900-exam-objectives.md.

Repository Structure

ai900/
├── .github/                        # GitHub config (CODEOWNERS, templates, Copilot agents)
│   ├── agents/                     # GitHub Copilot agent definitions
│   ├── instructions/               # Copilot custom instructions
│   ├── prompts/                    # Copilot prompt files
│   └── ISSUE_TEMPLATE/
├── bicep/                          # CAF-aligned IaC for lab environment
│   ├── main.bicep
│   ├── modules/                    # ai-services, openai, doc-intel, ML, etc.
│   └── parameters/                 # dev.bicepparam, prod.bicepparam
├── demos/                          # Live class demos (Python + uv)
│   ├── .env.example                # Template for Azure credentials
│   ├── assets/                     # Shared media & datasets (LFS-tracked)
│   │   ├── Audio-Video/
│   │   ├── CSV/
│   │   ├── OCR/
│   │   ├── People/
│   │   ├── Places/
│   │   └── Things/
│   ├── hour-1-ai-fundamentals/     # Vision, Content Safety, Responsible AI
│   ├── hour-2-machine-learning/    # scikit-learn classification/regression/clustering
│   ├── hour-3-computer-vision/     # Image Analysis, OCR, Face, Document Intelligence
│   ├── hour-4-nlp/                 # Sentiment, NER, Speech, CLU
│   └── hour-5-generative-ai/      # GPT-4o, DALL-E 3, prompt engineering, RAG
├── docs/                           # Course materials & exam prep
│   ├── warner-ai900-feb-2026.pptx  # Slide deck (current delivery)
│   ├── AI-900-exam-objectives.md   # Full objective domain
│   ├── AI-900-CORE-RESOURCES.md    # Curated study materials
│   ├── AI-900-PRACTICE-QUESTIONS.md
│   ├── AI-900-PRACTICE-QUESTIONS-SET2.md
│   ├── PRACTICE-QUESTIONS-GUIDE.md # Practice exam resources
│   ├── MCP-DOCS-SERVER-GUIDE.md    # Claude AI + MS Docs for cert prep
│   ├── INDEX.md                    # Guided tour of all materials
│   ├── LEARNING_RESOURCES.md
│   └── exam-metadata/
├── feb-2026/                       # Current delivery course plan
│   ├── course-plan-feb-2026.md
│   └── to-be-archived/            # Legacy content staged for removal
├── images/                         # README cover images
├── practice-questions/             # Practice questions by domain
│   ├── 01-ai-workloads-and-considerations/
│   ├── 02-machine-learning-on-azure/
│   ├── 03-computer-vision-workloads/
│   ├── 04-nlp-workloads/
│   └── 05-generative-ai-workloads/
├── scripts/                        # Utility scripts
│   ├── deploy-ai-services.sh
│   ├── cleanup-ai-services.sh
│   ├── validate-links.py
│   └── github-cli.ps1
└── temp/                           # Temporary working files

Running the Demos

Each demo is a standalone Python project managed with uv. You need Python 3.13+ and uv installed.

cd demos/hour-1-ai-fundamentals
uv sync                   # creates .venv and installs dependencies
uv run python main.py     # launches interactive menu

Repeat for any hour-N-* folder. All demos share a single demos/.env file for Azure credentials:

cp demos/.env.example demos/.env
# Fill in your Azure AI Services keys and endpoints

Bicep Deployment

Deploy the full lab environment with one command:

az deployment group create \
  --resource-group AI900-Feb2026 \
  --template-file bicep/main.bicep \
  --parameters bicep/parameters/dev.bicepparam

Azure Terminology (Current as of May 2025)

The exam uses current Azure service names exclusively. Deprecated names appear only as wrong answers.

Deprecated Name	Current Name
Cognitive Services	Azure AI Services
LUIS	CLU (Conversational Language Understanding)
QnA Maker	Custom Question Answering
AI Studio	Microsoft Foundry (ai.azure.com)
Language Studio	Deprecated – use Microsoft Foundry portal

Key Azure Portals

Portal	URL	Notes
Azure Portal	portal.azure.com	Resource management
Microsoft Foundry	ai.azure.com	Primary for Language, GenAI, model catalog
Azure ML Studio	ml.azure.com	AutoML, Designer, endpoints
Vision Studio	portal.vision.cognitive.azure.com	Image Analysis, OCR, Face
Speech Studio	speech.microsoft.com	Speech-to-text, text-to-speech
Custom Vision	customvision.ai	Image classification, object detection

Study Resources

In This Repo

• Practice Questions Guide – 15 practice exam resources and study strategies
• AI-900 Core Resources – Curated study materials, practice exams, MS Learn paths
• MCP Microsoft Docs Server Guide – Use Claude AI + MS Docs for interactive cert prep
• Docs Index – Guided tour of all course materials

Microsoft Learn Path

• Introduction to AI in Azure – 14-module learning path covering all five exam domains

Register for Exam

• Pearson VUE Exam Registration
• Microsoft Certification Deals

Prerequisites

• Basic understanding of cloud computing concepts
• Microsoft Azure subscription (free trial or paid)
• Python 3.13+ and uv for running demos
• Interest in artificial intelligence and machine learning

Instructor

• Name: Tim Warner
• Title: Microsoft MVP & Certified Trainer
• Website: techtrainertim.com
• LinkedIn: Timothy Warner

License

This course material is licensed under the MIT License. See the LICENSE file for details.