Numerical Analysis (CS 450) Fall 2021
What | Where |
---|---|
Time/place | Tue/Thu 11:00am--12:15pm 0027/1025 Campus Instructional Facility / Catalog |
Class URL | https://bit.ly/cs450-f21 |
Class recordings | Illinois Mediaspace |
Live Lecture | Meeting Link |
Online Office Hours | Meeting Link (on Zoom) |
Web forum | Discuss » · Help Desk |
Instant Message | Send » |
Calendar | View » |
Quizzes
Older quizzes
- Quiz for lecture 25
- Quiz for lecture 24
- Quiz for lecture 23
- Quiz for lecture 22
- Quiz for lecture 21
- Quiz for lecture 20
- Quiz for lecture 19
- Quiz for lecture 18
- Quiz for lecture 17
- Quiz for lecture 16
- Quiz for lecture 15
- Quiz for lecture 14
- Quiz for lecture 13
- Quiz for lecture 12
- Quiz for lecture 11
- Quiz for lecture 10
- Quiz for lecture 9
- Quiz for lecture 8
- Quiz for lecture 7
- Quiz for lecture 6
- Quiz for lecture 5
- Quiz for lecture 4
- Quiz for lecture 3
- Quiz for lecture 2
You can also find past quizzes under their corresponding lecture in the class calendar.
Homework
- Homework Set 1 (due: Sep 1, 2021, 10pm)
- Homework Set 2 (due: Sep 8, 2021, 10pm)
- Homework Set 3 (due: Sep 22, 2021, 10pm)
- Homework Set 4 (due: Sep 29, 2021, 10pm)
- Homework Set 5 (due: Oct 15, 2021, 10pm)
- Homework Set 6 (due: Oct 20, 2021, 10pm)
- Homework Set 7 (due: Nov 3, 2021, 10pm)
- Homework Set 8 (due: Nov 12, 2021, 10pm)
- Homework Set 9 (due: Dec 1, 2021, 10pm)
- Homework Set 10 (due: Dec 8, 2021, 10pm. May be turned in without penalty until Dec 10, 2021 10pm.)
4-Credit Hour Assignment
- Assignment 1 (4-credit hour) (due: Nov 9, 2021, 10pm)
- Assignment 2 (4-credit hour) (due: Dec 8, 2021, 10pm. May be turned in without penalty until Dec 10, 2021 10pm.)
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.
Course Outline
- lec01-2021-08-24.pdf
- lec02-2021-08-26.pdf
- lec03-2021-08-31.pdf
- lec04-2021-09-02.pdf
- lec05-2021-09-07.pdf
- lec06-2021-09-09.pdf
- lec07-2021-09-14.pdf
- lec08-2021-09-16.pdf
- lec09-2021-09-21.pdf
- lec10-2021-09-23.pdf
- lec11-2021-09-28.pdf
- lec12-2021-09-30.pdf
- lec13-2021-10-05.pdf
- lec14-2021-10-07.pdf
- lec15-2021-10-12.pdf
- lec16-2021-10-14.pdf
- lec17-2021-10-19.pdf
- lec18-2021-10-21.pdf
- lec19-2021-10-26.pdf
- lec20-2021-10-28.pdf
- lec21-2021-11-02.pdf
- lec22-2021-11-04.pdf
- lec23-2021-11-09.pdf
- lec24-2021-11-11.pdf
- lec25-2021-11-16.pdf
- lec26-2021-11-18.pdf
- lec27-2021-11-30.pdf
- lec28-2021-12-02.pdf
- lec29-2021-12-07.pdf
Team
Textbook
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
Also see our class Piazza forum for a discount code for purchasing the book from SIAM.
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 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.
Another way to obtain a Python installation is through a virtual machine image:
Grading Policies
Python Help
(see section 1 of the outline for more)
- Python tutorial
- Facts and myths about Python names and values
- Learn Python the hard way
- Project Euler (Lots of practice problems)
- From Python to Numpy
- PythonTutor (Execute Python step-by-step, with pictures)
Python workshop material
- Video: Located on Echo 360 along with the other class recordings
- Tutorial material
- Scipy lecture notes
- CSE workshop training material
Numpy Help
(see section 1 of the outline for more)
- Introduction to Python for Science
- The SciPy lectures
- The Numpy MedKit by Stéfan van der Walt
- The Numpy User Guide by Travis Oliphant
- Numpy/Scipy documentation
- More in this reddit thread
- An introduction to Numpy and SciPy