MATH 504 / CS 575: Numerical Linear Algebra

Time and Place: MWF 11:00 am - 11:50 am, on MS Teams
Instructor: Jehanzeb H. Chaudhry (Zeb), jehanzeb@unm.edu, www.math.unm.edu/~jehanzeb
Office Hours: Mon: 1-2pm, Wednesday: 1-3pm (on MS Teams or Zoom)

Lecture Delivery The lectures will be delivered via MS Teams. You need to join the Math 504 / CS 375 team at this link. Please make sure you have joined the team before classes start.

Syllabus

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

*Python

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. You can do your entire homework in Jupyter Notebooks , which combine your text, figues and code in one single file.

*Python and Numpy Help

Python tutorial (https://docs.python.org/3/tutorial/index.html)
Facts and myths about Python names and values (http://nedbatchelder.com/text/names.html)
The Numpy MedKit (http://mentat.za.net/numpy/numpy_advanced_slides/)
Spyder (a Python IDE, like Matlab)

An introduction to Numpy and SciPy (http://www.engr.ucsb.edu/~shell/che210d/numpy.pdf)
Jupyter Notebooks (https://jupyter.org/) or better still Jupyter Lab (https://jupyterlab.readthedocs.io/en/stable/")

*Matlab

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.

Homeworks: The homeworks will have both a computational and theoretical component. Late homeworks will not be accepted.