Brandeis Math 162a is a graduate course the provides a broad overview of scientific computing.

This Git repository contains example codes from the course. The codes are primarily written in Python, and make use of several commonly-used libraries

• NumPy for numerical linear algebra (www.numpy.org)
• SciPy for scientific routines and algorithms (www.scipy.org)
• Matplotlib for graphing and visualization (matplotlib.org)

The course is divided into six units:

• Unit 0: Overview of Scientific Computing
• Unit 1: Data Fitting
• Unit 2: Numerical Linear Algebra
• Unit 3: Asumptotics
• Unit 4: Numerical Methods for Ordinary Differential Equations
• Unit 5: Numerical Methods for Partial Differential Equations

Example codes from each unit are provided in separate directories.