MATH 504: Numerical Linear Algebra

Time and Place: Tuesday/Thursday 9:30 am - 10:45 am, SMLC 352
Instructor: Jehanzeb H. Chaudhry (Zeb),,
Office Hours: Tuesday: 1:30 - 3:00 pm, Wednesday: 9:00 - 10:30 am (SMLC 328)

Texts : Other Recommended Texts :

Course Description:   Direct and iterative methods of the solution of linear systems of equations and least squares problems. Error analysis and numerical stability. The eigenvalue problem. Descent methods for function minimization, time permitting. For each algorithm we investigate its efficiency, stability and accuracy. Efficient implementation of common algorithms in Numerical Linear Algebra and analysis of the effects of finite precision on stability. Master proof techniques commonly used in numerical linear alegebra (and numerical analysis in general).


Computation You can use either Python, Matlab or C/C++ for the computations.


I find Python along with the libraries numpy, scipy and matplotlib better than Matlab. Python has a very gentle learning curve, so you should feel at home even if you've never done any work in Python.

*Python and Numpy Help


  • A simple tutorial (intended for Math 375) MATLAB tutorial (PDF) script with all commands(matlab_tutorial.m) ApproxExp.m f1.m df1.m MyDeriv.m my_funky_fcn.m
  • MTU
  • MIT
  • *C/C++

    C/C++ is like a double shot espresso. If you don't know what it is, its better to steer clear.


    60-70% Homework
    0-10% Class Participation
    30% Exams (10% for Midterm + 20% for Final)

    Weights: Maximum of

    After the above weighted score has been calculated, letter grades will be assigned according to the following scheme: A, 90 or above, B, 80 or above, C, 70 or above, D, 60 or above, F below 60. However, the instructor reserves the right to “curve” grades to offset unforeseen circumstances. The curving of grades will never decrease a student’s letter grade below that given by the above formula.

    Important Dates:  
    Midterm Exam :   March 2 (Thursday), in Class
    Final Exam:   May 9 (Tuesday), 7:30 am - 9:30 am (Ouch!)

    Notes Week 1  Week 2  Week 3  Week 4  Weeks-5-6  Week-7  lost count 1  lost count 2  Eigenvalues  Classical Iterative Solvers  CG  GMRES etc  Remaining Items 

    Homeworks: The homeworks will have both a computational and theoretical component. Late homeworks will not be accepted.
    Computational Exercises
    Homework 1 (Already!?)
    Homework 2
    Homework 3
    Homework 4 and 5
    Homework 6
    Homework 7   hw7_svd.m
    Homework 8  
    Homework 9  
    Homework 10  
    Homework 11   generate_2d_poisson_mat_rhs.m