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Numerical Analysis (CS 450) Spring 2016

What Where
Time/place MWF 9:00am-9:50am 1404 Siebel / Catalog
Class URL https://bit.ly/cs450-s16
Class recordings Echo 360
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Quizzes

Please find the quizzes under their corresponding lecture in the class calendar.

Exams

Please find information on our upcoming exams in the corresponding section of the class calendar. Reserve your time slots in the testing facility as soon as possible--otherwise your preferred times may no longer be available.

Homework

Project

Course Outline

CAUTION!

These scribbled PDFs are an unedited reflection of what I wrote during class. They need to be viewed in the context of the class discussion that led to them. See the lecture videos for that.

If you would like actual, self-contained class notes, look in the outline above.

These scribbles are provided here to provide a record of our class discussion, to be used in perhaps the following ways:

  • as a way to cross-check your own notes
  • to look up a formula that you know was shown in a certain class
  • to remind yourself of what exactly was covered on a given day

By continuing to read them, you acknowledge that these files are provided as supplementary material on an as-is basis.

Team

Andreas Kloeckner

Andreas Kloeckner

(Instructor)

Email: andreask@illinois.edu

Office: 4318 Siebel


Lishen He

Lishen He

(TA)

Email: lhe10@illinois.edu


Peter Sentz

Peter Sentz

(TA)

Email: sentz2@illinois.edu


Matt Wala

Matt Wala

(TA)

Email: wala1@illinois.edu


Textbook


Scientific Computing: An Introductory Survey
Scientific Computing: An Introductory Survey

Michael T. Heath, Second Edition, McGraw-Hill.

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.

Virtual Machine Image

While you are free to install Python and Numpy on your own computer to do homework, the only supported way to do so is using the supplied virtual machine image.

Download Virtual Machine »

Grading Policies

View policies »

Previous editions of this class

Python Help

(see section 1 of the outline for more)

Python workshop material

Numpy Help

(see section 1 of the outline for more)