# APh/MS 141

**Source**: https://aph.caltech.edu/academics/courses/aphms-141
**Parent**: https://aph.caltech.edu/academics/courses

APh/MS 141\

Introduction to Computational Methods for Science and Engineering

9 units (3-0-6) 
|
third term

Prerequisites: graduate standing or instructor's permission.

A broad introduction to scientific computing using Python. Introduction to Python and its packages Numpy, SciPy, and Matplotlib. Numerical precision and sources of error. Root-finding and optimization. Numerical differentiation and integration. Introduction to numerical methods for linear systems and eigenvalue problems. Numerical methods for ordinary differential equations. Finite-difference methods for partial differential equations. Discrete Fourier transform. Introduction to data-driven and machine learning methods, including deep learning using Keras and Tensorflow. Introduction to quantum computing using Qiskit and IBM-Q. Students develop numerical calculations in the homework and in midterm and final projects.

Instructor:
Bernardi