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Docker Essentials Guide

Master Docker for AI applications: build optimized images, containerize FastAPI + LLM apps, orchestrate multi-service stacks with Docker Compose (API + ChromaDB + Redis), and apply production best practices including multi-stage builds, secrets management, and health checks. Your gateway to production deployment.

64
lessons
8
modules
English · Spanish
available in
Yes
certificate
Free
access
NIEVA

Outcomes

What you'll be able to do

  • Understand Docker architecture and run your first containers
  • Write Dockerfiles that build optimized images for Python AI applications
  • Manage persistent data with volumes and connect containers via networking
  • Containerize FastAPI + OpenAI apps with proper secrets and environment management
  • Orchestrate multi-service AI stacks with Docker Compose (API + ChromaDB + Redis)
  • Apply multi-stage builds to reduce AI image sizes from 2GB to 200MB
  • Implement security best practices: non-root users, secrets management, image scanning
  • Build production-ready AI stacks with health checks and restart policies

Before you start

What you need to bring

It's for you if...

  • AI Engineers who need to containerize their applications for team collaboration and deployment
  • Backend developers building AI features who need reproducible development environments
  • Developers transitioning from local development to production deployment workflows
  • Teams that want consistent environments across development, staging, and production
  • Anyone following the AI Engineering Path who needs Docker for CI/CD and cloud deployment

Requirements and materials

  • Python intermediate (used throughout the AI Engineering Path)
  • Experience building REST APIs with FastAPI (Guide #3)
  • Basic command line proficiency (navigation, files, permissions)
  • No prior Docker experience required

Content

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