AI applications often fail outside development environments due to dependency mismatches, missing configurations, and inconsistent runtime setups. This course solves that problem by teaching how to containerize, deploy, and scale AI applications using Docker.

Instead of generic Docker examples, every concept is taught through real AI use cases—from a CLI chatbot to a full multi-service AI system. You will learn how to package applications with Docker, manage persistent data using volumes, connect services via Docker networking, and orchestrate complete AI stacks using Docker Compose.

The course culminates in a production-grade capstone project: a fully containerized Document Q&A system using FastAPI, Redis, ChromaDB, and Nginx. By the end, you will have the skills to reliably ship AI applications across any environment with consistent performance and reproducibility.