How to Docker
Beginner
~60 minutes
$10.00
docker
python
mlops
devcontainers
containerization
This hands-on introduction to Docker for AI/ML (~1 hour) covers containerization fundamentals through three progressive labs, culminating in creating and publishing your own ML development environment.
What you'll learn
- Docker basics - Images, containers, Dockerfiles, and key concepts
- Building containers - From simple scripts to web applications
- Development containers - Creating portable, shareable ML dev environments
- Publishing images - Sharing your work via Docker Hub
- Portability - Verifying your environment works anywhere (GitHub Codespaces)
Hands-on labs
- Lab 1: Data cleaner - Build a containerized Pandas-based data cleaning script
- Lab 2: Streamlit app - Run an interactive data visualization dashboard in a container
- Lab 3: ML dev container - Create, customize, and publish your own ML dev environment
Prerequisites
- Docker installed (Get Docker)
- Docker Hub account (Sign up)
- VS Code with Remote-Containers extension (recommended)
- GitHub account (for Codespaces verification)
- Basic Python and command line knowledge
Interest list
1 / 20
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