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Numerical Analysis (CS 450) Spring 2018

What Where
Time/place WF 1:00pm-2:15pm 1404 Siebel / Catalog
Class URL https://relate.cs.illinois.edu/course/cs450-s18/
Class recordings View Echo 360 Video »
Web forum View Piazza »
Calendar View Calendar »

Quizzes

The latest five quizzes will be posted below. To access all previous quizzes, go to (Participant, View Grades, follow desired flow grade link, follow arrow flow link),

Quiz 10: Sensitivity of Eigenvalue Problems and Krylov Subspace Methods »

Quiz 9: Solving Eigenvalue Problems by Similarity Transformations »

Quiz 8: Basics of Eigenvalue Problems »

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

Homeworks will be posted here generally on a biweekly basis. They will usually be due at 10 pm Thursdays.

Homework 3 » 4 Credit-Hour Addendum to Homework 3 »

Homework 2 » 4 Credit-Hour Addendum to Homework 2 »

Homework 1 » 4 Credit-Hour Addendum to Homework 1 »

Assignments for 4 Credit-Hour Section

If you are enrolled in CS 450 for 4 credit hours, you will need to complete (typically one) additional question along with each homework assignments. Registration for the section has been opened for undergraduates as well. Students enrolled in the 3 credit hour section can complete the additional problems for some extra credit points.

Course Outline

Team

Edgar Solomonik

Edgar Solomonik

(Instructor)

Email: solomon2@illinois.edu

Office: 4229 Siebel

Yizhi (Yeech) Zhu

Yizhi (Yeech) Zhu

(TA)

Email: yzhu44@illinois.edu

Office: 0207 Siebel

Pedro D. Bello-Maldonado

Pedro D. Bello-Maldonado

(TA)

Email: belloma2@illinois.edu

Office: 0207 Siebel

Yuchen Su

Yuchen Su

(TA)

Email: yuchens6@illinois.edu

Office: 0207 Siebel

Bogdan Enache

Bogdan Enache

(TA)

Email: enache2@illinois.edu

Office: 0207 Siebel

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 »

Quiz: Policies »

Previous Editions of CS 450

Additional Text Resources

Python Help

(see section 1 of the outline for more)

Python Workshop Material

Numpy Help

(see section 1 of the outline for more)