Docker
Container packaging for reproducible ML and AI deployments.
Maturity level: L3 — Can Deploy
Six perspectives on Docker
Roadmap
First container skill — learn before Kubernetes.
Architecture
Packages models, APIs, and workers into portable units.
Company
Near-universal expectation for backend and platform-oriented roles.
Projects
Dockerize every API and training job you build.
Interview
Explain images, layers, and production Dockerfile best practices.
Career
Foundation for all production AI engineering paths.
What & Why
What: Platform for building, shipping, and running applications in containers.
Why: Eliminates 'works on my machine' — essential for ML model serving and CI/CD.
Build this
Containerize a FastAPI ML service with optimized image layers.
Production reality
- ! Large images slowing deploys
- ! Wrong base image
- ! Secret leakage in layers
- ! Volume permission issues
Interview preparation
- Image layering and cache optimization
- Multi-stage builds for Python ML apps
- Container security basics
Connected skills
Explore Docker in the interactive universe or train with live cohorts.
Want this Docker learning path turned into your own plan?
A roadmap shows the destination. In 1:1 mentorship I turn it into a week-by-week learning path for your background, review your projects, and prepare you for interviews until you land the role. Online, in your time zone.
Start with one 60-minute 1:1 call: .
Prefer a structured live course? Join the MLOps · AIOps · LLMOps · Agentic AI masterclass →