Welcome to MLOps Zero to Hero — a complete, hands-on repository designed to take you from beginner to industry-ready in Machine Learning Operations (MLOps).

This repo contains structured modules, real-world workflows, and learning resources to help you master the end-to-end MLOps lifecycle — from model development to deployment, monitoring, and automation.

This repository walks you through:

• Introduction to MLOps
• Role of MLOps in modern ML systems
• Core principles and best practices

• Versioning and experiment tracking
• Model evaluation and metrics

• Serving models using KServe & SageMaker
• Containerization with Docker
• Deployment patterns

• GitHub Actions automation
• Continuous model training, packaging, and serving
• Synchronizing deployments using GitOps (Argo CD)

• AWS S3 model storage
• Service account configurations
• Production-ready deployment pipelines