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MLOps + Cloud Deploy (AWS-First)

Advanced

Ship ML like software: Docker reproducibility, FastAPI serving with smoke tests, experiment tracking + registry, CI/CD build gates, monitoring/drift with K8s reading literacy, and a flagship deployed pipeline on a free-tier cloud with cold-clone reproducibility proof. AWS-first with GCP parity notes.

MLOps + Cloud Deploy (AWS-First)
Duration

6 weeks

Content

6 modules, 19 lessons

Students

0

Total Time

~6 hours

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Course Curriculum

1

M0 — Reproducibility + DockerFREE PREVIEW

Pinning, .dockerignore, cold-clone builds, and the 8-item reproducibility checklist the flagship re-uses.

55 min3 lessons
2

M1 — FastAPI Serving + Smoke TestsFREE PREVIEW

/health + /predict serving with pydantic validation and 5 containerized smoke tests.

57 min3 lessons
3

M2 — Experiment Tracking + RegistryFREE PREVIEW

MLflow-or-equivalent run logging, run comparison, promoted model cards.

34 min2 lessons
4

M3 — CI/CD BasicsFREE PREVIEW

Lint -> test -> build -> smoke pipeline with branch protections and a binding build gate.

45 min2 lessons
5

M4 — Monitoring/Drift + K8s ReadingFREE PREVIEW

Latency/error + PSI-style drift dashboards, alert rules, Deployment/Service reading literacy.

78 min3 lessons
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