Extension
Why keep learning?
Poor data management amplifies bias, brittle models and compliance risk. Regulators and customers increasingly expect explainable, auditable pipelines—not only high offline accuracy.

Dive deeper: additional materials
✨
Data lineage overview:
✨
Fairness in ML:
✨
Reproducibility tooling:
✨
Algorithmic bias:
Stretch project
Pick one production dataset and produce a one-page lineage sketch: sources, joins, PII handling, retention and known limitations. Share it with a peer for a red-team review.
In progress