Added rudimentary Teaching page and removed projects and repositories pages - add later when I have content.

Author: lvanveen

_pages/projects.md

@@ -2,11 +2,13 @@
 layout: page
 permalink: /teaching/
 title: teaching
-description: Materials for courses you taught. Replace this text with your description.
+description: A brief description of some of the courses I teach.
 nav: true
 nav_order: 6
 ---
 
-For now, this page is assumed to be a static description of your courses. You can convert it to a collection similar to `_projects/` so that you can have a dedicated page for each course.
-
-Organize your courses by years, topics, or universities, however you like!
+* Computational Science I. Aimed at second-year computer science and math students, this course treats a number of elementary algorithms for root finding, interpolation, differentiation, quadrature and optimization. We go in dome depth to investigate the stability, accuracy and efficiency both by means of analysis and by implementing and testing. All programming is done in Python (NumPy/Matplotlib/Pandas/...) and the students maintain their own repository for the assignments.
+* Computational Science II. Aimed at third-year math students (and, occasionally, physics and computer science students) this course treats more theory and is less focused on implementation and testing. We look at fixed point iteration, approximation by orthogonal polynomials and Fourier series, continuation methods and other somewhat more advanced methods.
+* Ordinary Differential Equations. Aimed at second-year math and physics students, this course runs the gamut from single, autonomous ODEs to systems of nonlinear ODEs. Solution methods as well as qualitative methods are introduced. I like to throw in a few handfuls of modelling to help the students' intuition.
+* Partial Differential Equations. Aimed at fourth-year math students, this second course on PDEs goes into characteristics, shocks, entropy solutions, Green's functions and generalized eigenproblems.
+* High Performance Computing. A grad-level course the treats as much as possible of basic scientific programming, using libraries, code optimization and debugging, MPI and OpenMP parallelism and offloading to GPU devices. Towards the end of the course, the students use the shared super computing facilities of Alliance Canada.