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Numerical Analysis (CS 450) Spring 2023

What Where
Time/place Tue/Thu 11:00am--12:15pm [1404 Siebel Center]
Class URL
Class recordings
Web forum (see lecture 1 recording or email instructor for join code)


Due at the start of each lecture (latest 5 posted here), posted by 5 pm day of prior lecture.

Quiz 20: Composite Quadrature and Numerical Differentiation »

Quiz 21: Characterization of ODEs and Euler Methods »

Quiz 22: Initial Value Problems for Ordinary Differential Equations »

Quiz 23: Methods for Ordinary Differential Equation BVPs »

Quiz 24: BVPs and Classification of PDEs »


Homework 1 »

Homework 2 »

Homework 3 »

Homework 4 »

Homework 5 (Extra Credit for both sections, 1/3 value of main part of regular homework) »

4-Credit Hour Homeworks

For the 4-credit hour section, addendum problems are worth 1/4 of the total credit for each assignment. For the 3-credit hour section, these problems may be completed for extra credit, with half of the value (1/6 of the assignment value).

4-Credit Hour Addendum to Homework 1 »

4-Credit Hour Addendum to Homework 2 »

4-Credit Hour Addendum to Homework 3 »

4-Credit Hour Addendum to Homework 4 »

Course Outline


Edgar Solomonik

Edgar Solomonik



Office: Siebel 4229, Monday 11-12

Lukas Spies

Lukas Spies



Office: Zoom, Tuesday/Thursday 3-4pm

Patrick Naughton

Patrick Naughton



Office: Siebel 0207, Thursday 2-3pm, Friday 2-3pm

Navjot Singh

Navjot Singh



Office: Siebel 0207, Wednesday 2-3pm, Friday 3-4pm

Statement on CS CARES, Values, and Code of Conduct

All members of the Illinois Computer Science department---faculty, staff, and students---are expected to adhere to the CS Values and Code of Conduct. The CS CARES Committee is available to serve as a resource to help people who are concerned about or experience a potential violation of the Code. If you experience such issues, please contact the CS CARES Committee. The instructor of this course are also available for issues related to this class.


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 »

Grading Policies

View policies »

Python Help

(see section 1 of the outline for more)

Python workshop material

Numpy Help

(see section 1 of the outline for more)