MLOps Code Examples

This repository contains learning activities and code examples from the MLOps course.

Repository Structure

Each module has its own directory containing hands-on exercises:

module1/    # ML Fundamentals & Development Environment
module2/    # Model Serving & APIs
module3/    # Containerization & CI/CD
module4/    # Pipeline Orchestration & Experiment Tracking
module5/    # Cloud Deployment & Scaling
module6/    # LLM Serving & Optimization
module7/    # RAG & Agentic AI
module8/    # Monitoring & Governance

Getting Started

Each subdirectory contains:

• mwe/ - Minimal Working Examples with step-by-step instructions
• lab/ - Lab exercises (where applicable)
• README.md files with setup and usage instructions

Navigate to any example directory and follow its README for instructions.

Requirements

Most examples require:

• Python 3.10+
• Docker (for containerized examples)
• See individual requirements.txt files for specific dependencies

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

You are free to:

• Share — copy and redistribute the material in any medium or format
• Adapt — remix, transform, and build upon the material

Under the following terms:

• Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made
• NonCommercial — You may not use the material for commercial purposes
• ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license

See the LICENSE file for details.