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 28: Methods for Solving Sparse Linear Systems »
Quiz 27: Numerical Methods for PDEs »
Quiz 26: Methods for Solving ODE BVPs »
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 7 » 4 Credit-Hour Addendum to Homework 7 »
Homework 6 » 4 Credit-Hour Addendum to Homework 6 »
Homework 5 » 4 Credit-Hour Addendum to Homework 5 »
Homework 4 » 4 Credit-Hour Addendum to Homework 4 »
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
- 1. Chapter 1: Scientific Computing
- Notes (Michael T. Heath)
- Lecture Notes
- 2. Chapter 2: Systems of Linear Equations
- Notes (Michael T. Heath)
- 3. Chapter 3: Linear Least Squares
- Notes (Michael T. Heath)
- 4. Chapter 4: Eigenvalue Problems
- Notes (Michael T. Heath)
- 5. Chapter 5: Nonlinear Equations
Team
Textbook
Scientific Computing: An Introductory Survey
Michael T. Heath, Second Edition, McGraw-Hill.
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.
Previous Editions of CS 450
Additional Text Resources
- Linear Algebra and Its Applications Gilbert Strang, 4th Edition, Harcourt Brace, 1987 (on reserve at Grainger).
- Numerical Linear Algebra Lloyd Trefethen and David Bau, SIAM, 1997 (on reserve at Grainger).
- Applied Numerical Linear Algebra James Demmel, SIAM, 1997.
- Matrix Computations Gene Golub and Charles Van Loan, 4th Edition, The John's Hopkins University Press, 2013.
- Numerical Recipes William Press, Saul Teukolsky, William Vetterling, and Brian Flannery, 3rd Edition, Cambridge University Press, 2007.
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)
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
- Spyder (a Python IDE, like Matlab) is installed in the virtual machine. (Applications Menu > Development > Spyder)
- An introduction to Numpy and SciPy