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Numerical Analysis (CS 450) Fall 2020

What Where
Lecture (via Zoom) Tu/Th 11:00am-12:15pm CT (UTC-5 to Nov 1, UTC-6 from Nov 1)
Class URL https://relate.cs.illinois.edu/course/cs450-f20/
Instructor Luke Olson
Quick Links

Learning Goals for CS 450

FAQ

Lectures will be delivered through Zoom (link below) from 11-12:15 Tu/Th. It is best to arrive say 5 minutes beforehand -- the lectures will intend on starting promptly at 11. They will include a combination of demos, hands-on activities, and discussion.

Yes! All lectures will be posted on MediaSpace

We'll be using the #lecture room in Campuswire for discussions during lecture.

With everything online, there's a need to chat and discuss~---~we've selected Campuswire as it adds functionality of both Slack/Discord and Piazza, as well as adding FERPA compliance. Relate will be your main source of content, delivering homework, quizzes, and exams, as well as hosting your grades.

We'll have recorded videos. If Zoom goes down with enough warning, then we'll turn to a service such as Jitsi.

Exams will be proctored online, through the Computer Based Testing Facility (CBTF).

Quizzes are due before 11am on the day of the lecture.

Quizzes are not auto-submitted. You must click the green check mark and fully submit your quiz to receive credit.

Homework is due before 5pm each week (homework is due Friday).

Exam Scheduling

CBTF Instructions Link

Exam Registration Link

Team


Luke Olson

Luke Olson

(Instructor)

Email: lukeo@illinois.edu

Shelby Lockhart

Shelby Lockhart

(Teaching Assistant)

Email: None

Office Hours: T/Th 9:00 CST, W 8:00 CST

Yuchen Pang

Yuchen Pang

(Teaching Assistant)

Email: None

Office Hours: M/Th 13:00 CST, W 9:00 CST

Linjian Ma

Linjian Ma

(Teaching Assistant)

Email: None

Office Hours: M 15:00 CST, T 13:00 CST, W 21:00 CST

Lukas Spies

Lukas Spies

(Teaching Assistant)

Email: None

Office Hours: M/W 14:00 CST, T 21:00 CST


Textbook


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


Computing

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 relate 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)