AI-300 Lab Guide

Hands-on guide for the Microsoft AI-300: Operationalizing Machine Learning and Generative AI Solutions exam.

All 13 labs from the official Microsoft Learn curriculum, reorganized into runnable Jupyter notebooks with standalone Python SDK scripts, architecture diagrams, cost estimates, and exam tips.

Attribution: All lab content is adapted from Microsoft Learning. See ATTRIBUTION.md for details.

Architecture Overview

Who This Is For

• Preparing for the AI-300 exam
• Have an Azure subscription (pay-as-you-go is fine)
• Comfortable with CLI basics (each lab explains what you need)

Quick Start

1. Clone this repo: git clone https://github.com/btriani/ai-300-lab-guide.git
2. Run the prerequisites check: ./scripts/check-prerequisites.sh
3. Install MLOps dependencies: pip install -r mlops/requirements.txt
4. Provision MLOps infrastructure: ./scripts/setup-mlops.sh
5. Start with Lab 01

Labs

MLOps Track

#	Lab	Notebook	Est. Cost	Est. Time
01	AutoML + MLflow	lab01-automl-mlflow.ipynb	~$1-2	30 min
02	Scripts & Command Jobs	lab02-scripts-command-jobs.ipynb	~$0.50	15 min
03	Hyperparameter Tuning	lab03-hyperparameter-tuning.ipynb	~$0.50	20 min
04	Pipelines	lab04-pipelines.ipynb	~$0.50	20 min
05	Plan & Prepare MLOps	lab05-plan-prepare-mlops.ipynb	~$2-4	30 min
06	GitHub Actions	lab06-github-actions.ipynb	~$0.50	25 min
07	Deploy & Monitor	lab07-deploy-monitor.ipynb	~$2-5	45 min

GenAIOps Track

#	Lab	Notebook	Est. Cost	Est. Time
08	Foundry Setup	lab08-foundry-setup.ipynb	~$1-2	20 min
09	Prompt Versioning	lab09-prompt-versioning.ipynb	~$0.50	30 min
10	Prompt Optimization	lab10-prompt-optimization.ipynb	~$1-2	40 min
11	Automated Evaluation	lab11-automated-evaluation.ipynb	~$5-10	40 min
12	Monitoring & Tracing	lab12-monitoring-tracing.ipynb	~$1-2	40 min
13	Fine-Tuning Strategies	lab13-fine-tuning.ipynb	Free	15 min

Total estimated cost: ~$15-30 | Total time: ~6 hours

See COST-GUIDE.md for per-service pricing and how to minimize spend.

Cheatsheets

• MLOps Cheatsheet -- CLI commands, key concepts, common patterns
• GenAIOps Cheatsheet -- azd commands, Foundry concepts, evaluation patterns

Scripts

Script	Purpose
scripts/check-prerequisites.sh	Verify all tools are installed
scripts/setup-mlops.sh	One-command MLOps infrastructure setup
scripts/setup-genaiops.sh	One-command GenAIOps infrastructure setup
scripts/cleanup-all.sh	Delete all Azure resources when done

Official Microsoft Resources

• MLOps Labs (original)
• GenAIOps Labs (original)
• AI-300 Exam Page

License

MIT -- see ATTRIBUTION.md for Microsoft source attribution.