What this Course is Not

This is not a course in Numerical Analysis. Courses in Numerical Analysis are taught by the Department of Mathematics, see, for example, M471 (Numerical Analysis I), M472 (Numerical Analysis II), M568 (Time Series Analysis), M571 (Analysis of Numerical Methods I), M572 (Analysis of Numerical Methods II), M671 (Numerical Treatment of Differential and Integral Equations I), M672 (Numerical Treatment of Differential and Integral Equations II), M771 (Selected Topics in Numerical Analysis I), and M772 (Selected Topics in Numerical Analysis II). Neither is this a course in Computational Physics. This subject is taught by the Department of Physics, see, for example P410 (Computing Applications in Physics), P609 (Computational Physics), and P700 (Topics Course: Monte Carlo Methods in Physics). This is not a course in Computational Chemistry, Geophysics, Optics and Engineering either. All those topics are covered by respective schools - no doubt better than I ever could do so myself.

Furthermore, selected topics of the Syllabus that are covered by those courses, will not be covered by this one.

This course will teach you stuff that none of the other courses does.

A course in Numerical Analysis or in Computational Physics, more often than not, will single out a particular computational tool that the lecturer feels most comfortable with. This is usually Matlab, Mathematica, and/or Maple. Since the purpose of the course is to teach Numerical Analysis and not computer tools, the tool of choice will be used to cover most of the subject.

This course, on the other hand, will focus primarily on the tools and computing methodologies of relevance to Scientific Computing, because it is a course in Computer Science. Therefore, rather than covering broadly a subject of Numerical Analysis, and narrowly a subject of computing tools, i.e., teach you just one or two, we will cover narrowly (if at all) some selected subjects of Numerical Analysis (or Physics, or Chemistry, or Geophysics, or Engineering, $\ldots$), and broadly the tools themselves, i.e., we will study many of them - as you would study many different numerical methods in the course of Numerical Analysis.

If time allows, and if there are still any students left, we will delve right into the guts of some tools too, i.e., we will study how they are designed and implemented.