Computational Analysis: A Reproducible Python Course for Numerical Methods

This repository provides a fully reproducible Python-based computational analysis course covering numerical linear algebra, optimization, ordinary and partial differential equations, and data-driven modeling.

The materials are designed for training students and researchers in modern computational workflows, including numerical stability analysis, algorithmic verification, and reproducible scientific computing using Jupyter notebooks.

The course is packaged as an executable Jupyter Book and is intended for use in academic instruction, research group onboarding, and independent study in computational science and engineering