Announcements | Syllabus | Assignments | Problem of the Day
Instructor: Charles Van Loan, 423 Gates, 255-5418, email@example.com. Office hours are here.
Meeting Time & Place: MWF 11:15-12:05, Phillips 307
Prerequisites: Computing assignments are in Matlab so a year's worth of programming in Python, Java, or C++ is more than enough. A solid understanding of linear algebra is essential. In that regard, here are some key words: Gaussian elimination, orthogonal matrix, eigenvalue, eigenvector, norms, independence, range, nullspace, basis. Happy to talk 1:1 if you have a concern about your background.
Description: 4 credits. Stable and efficient algorithms for linear equations, least squares, and eigenvalue problems. Direct and iterative methods are considered. The MATLAB system is used extensively.
Workload: There is a computing assignment every two weeks (approximately.) Associated with every lecture there is a "Problem of the Day" which should be worked out. They are not submitted for grading but you should take them very seriously. The POD's are a handy way to keep up with the course and to prepare for the final exam.
Related Courses: CS 5220 (Applications of Parallel Computers) by Professor David Bindel.
Text: Matrix Computations (4th Edition) by Golub and Van Loan
Grading: There are six Matlab Assignments, a take home midterm, and a final that has a take home part and a timed, closed-book written part. Final grade is based on the assignments (55%), the take-home midterm (15%), the take-home part of the final (15%), and the written part of the final (15%).
Software: GVL4 M-Files, The Pseudospectra Gateway, The University of Florida Sparse Matrix Collection
Some Linear Algebra References: Gil Strang's MIT Linear Algebra course videos and text are excellent. So is Carl Meyer's Matrix Analysis and Applied Linear Algebra book.
Some Matlab References: Insight Through Computing: A Matlab Introduction to Computational Science and Engineering (Van Loan and Fan), Getting Started with Matlab 7 (Pratap), Matlab: An Introduction with Applications (Gilat), Mastering Matlab7 ( Hanselman & Littlefield)
Computing: MATLAB is available on all public CIT Machines. The student edition of MATLAB is available from Mathworks.