Core Concepts:
Introduction to MLOps and CI/CD for ML.
Containerization with Docker and Kubernetes.
Deploying models on cloud platforms (AWS SageMaker, Azure ML, Google AI Platform).
Tools:
Docker, Kubernetes, Flask/FastAPI, AWS SageMaker, Azure ML, Google Cloud
Project:
Deploy a machine learning model as a REST API in a cloud environment and build a CI/CD pipeline for model updates.