You're not currently signed in. Sign in »

Numerical Analysis (CS 450) Fall 2019

What Where
Time/place MW 3:30pm--4:45pm 1320 DCL / Catalog
Class URL
Instructor Luke Olson

Course Outline


Luke Olson

Luke Olson




Scientific Computing: An Introductory Survey
Scientific Computing: An Introductory Survey / E-Book (accessible free of charge from campus network/VPN)

Michael T. Heath, Revised Second Edition, Society for Industrial and Applied Mathematics

Resource site

Also see our class Piazza forum for a discount code for purchasing the book from SIAM.


We will be using Python with the libraries numpy, scipy and matplotlib for in-class work and assignments. No other languages are permitted. Python has a very gentle learning curve, so you should feel at home even if you've never done any work in Python.

Running Code on your Own Computer

While running code in this online system should technically suffice to do your work for this class, you may find it useful to also install Python on your own computer.

The recommended and perhaps one of the easier ways of doing so involves downloading the Anaconda Python distribution. Note that this is a commercial product (even if it is free of charge), and this is not intended as an endorsement of the company or the product. Note that we cannot promise to provide technical support for this installation.

Download Anaconda Python »

Another way to obtain a Python installation is through a virtual machine image:

Download Virtual Machine »

Python Help

(see section 1 of the outline for more)

Python workshop material

Numpy Help

(see section 1 of the outline for more)