Welcome to the MLOps Curriculum! This repository contains materials for an extensive MLOps training program.

• Week 1: Introduction to MLOps and ML-DLC
  • Session 1: Introduction to MLOps
  • Session 2: Version Control
• Week 2: ML Reproducibility, Versioning, and Packaging
  • Session 3: Reproducibility
  • Session 4: Data Versioning Control
• ...

Follow these steps to get started with the MLOps curriculum.

• Create an account on GitHub.
• Install Git and set up GitHub according to the instructions in Session 2.

• Install Cookiecutter and initiate a new project following the steps in Session 3.

• Session 5: ML Pipelines and Experimentation Tracking
  • Recap of Pipelines - Credit Card Example
  • Writing dvc.yaml File
  • ...

• Session 7: Continuous Integration
  • Philosophy Behind CI/CD
  • Setting Up Github Actions for CI/CD
  • ...

• Session 9: Continuous Deployment
  • Recap of Continuous Integration
  • Continuous Delivery/Deployment
  • ...

• Session 10: Introduction to AWS
  • Introduction to AWS Machine Learning and MLOps Services
  • Pre-requisite
  • IAM
  • ...

• Session 12: Distributed Infrastructure
  • Understanding Distributed Computing
  • Docker and Microservices
  • ...

• Session 14: Deployment on Kubernetes
  • Deployment with Kubectl
  • Deployment Strategies
  • ...

• Session 16: Monitoring & Alerting
  • TBD
• Session 17: Rollout & Rollback Strategies
  • TBD
• Session 18: ML Technical Debt
  • TBD

• Session 6
• Session 7
• Session 8

This project is licensed under the MIT License.

Happy learning! 📚✨