Feature Engineering for Omics & Clinical Data — Hands-on

Design high-signal, trustworthy features for genomic, proteomic, metabolomic, imaging-derived, and clinical tabular data. This module focuses on rigorous preprocessing, leakage-safe splits, domain-aware transformations (e.g., gene-set activity scores) , selection and stability, and packaging features into reproducible pipelines ready for modeling and deployment.