Numerical computing is an interconnected combination of computer science and mathematics in which we develop and analyze algorithms for solving important problems in science, engineering, medicine, and business -- for example, simulating an earthquake, choosing a stock portfolio, or detecting cancer tumors in medical images. The students will learn principles and practices of basic numerical computation based on seven to eight mini-projects. This is a key aspect of scientific computation.
This class will cover several topics, including: graph clustering, graph partitioning, solving linear systems of equations, page rank algorithm and large-scale nonlinear optimization. As much as possible, numerical methods will be presented in the context of real-world applications.
A goal of the course is that students will learn principles and practices of basic numerical methods to enable scientific numerical simulations. This goal will be achieved within six to eight mini-projects with a focus on numerical computing.
40% of the grade is determined by mandatory graded project works and 60% is determined by a final written or oral exam during the official examination period.
Introduction to Computational Science
- A First Course in Numerical Methods by Uri Ascher and Chen Greif, published by the Society for Industrial and Applied Mathematics, available directly from SIAM.
- Numerical Computing with MATLAB, C. Moler (available online at http://www.mathworks.com/moler/chapters.html)
- Other material will be passed out as notes.