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MLOps Starter: FastAPI + Docker + CI/CD
Deploy an ML model as an API, containerize it, test it, and set up CI/CD basics for a production-grade delivery.
MLOpsFastAPIDockerCI/CDTesting
Duration
4 days
Format
Remote
Level
Intermediate
Key outcomes
- Design ML API contracts (schemas, validation, errors)
- Containerize correctly (reproducibility, image hygiene)
- Add tests for preprocessing + inference + API endpoints
- Create a simple CI pipeline with quality gates
Syllabus
Day 1 — API design for ML
- Prediction endpoints and schema validation
- Batch vs real-time inference patterns
- Logging, error handling, status codes
Day 2 — Containerization
- Dockerfile best practices (slim images, caching)
- Pinning dependencies and reproducibility
- Local build/run and environment parity
Day 3 — Testing
- Unit tests for preprocessing and inference
- Integration tests for API endpoints
- Contract tests and example payloads
Day 4 — CI/CD essentials
- Pipeline stages: lint/test/build
- Artifacts and simple release strategy
- Next steps: registry, environments, monitoring