🧠

MLOps Roadmap

From training a model in a notebook to running safe, observable ML systems in production.

Estimated time:3–5 months

1🌱

Phase 1 — ML & Software Foundations

Core ML concepts (train/val/test, overfitting)

2🧪

Dataset & feature versioning

Feature stores & train/serve skew

Reproducible training pipelines

3🚀

Model registries & staged promotion

Batch vs real-time inference serving

Canary/shadow rollout of new models

4📈

important

Data & concept drift detection

Model performance dashboards

Automated retraining triggers

Rollback strategy for bad model versions

Begin with interview questions to assess your current level.