CS111 Winter 2020—Introduction to Computational Science

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logo design: Yun Teng, CS111 Fall 2010

Introduction to computational science, emphasizing basic numerical algorithms and the informed use of mathematical software. Matrix computation, systems of linear equations, and differential equations. Students learn and use the numpy, scipy, and matplotlib libraries in Python.

lecture date description notes files
Tue Jan 07 Introduction; Ax=b: systems of linear equations lect01 Lecture Files
Thu Jan 09 Interesting matrices lect02 Lecture Files
Tue Jan 14 Solving Ax=b by LU factorization lect03 Lecture Files
Thu Jan 16 LU factorization: error, residual, complexity, partial pivoting lect04 Lecture Files
Tue Jan 21 Permutation vectors and matrices, SPD matrices, Cholesky lect05 Lecture Files
Thu Jan 23 Solving Ax = b by Jacobi and conjugate gradients lect06 Lecture Files
Tue Jan 28 Fitting data by least squares lect07 Lecture Files
Tue Feb 04 Data fitting by least squares with QR factorization lect08 Lecture Files
Thu Feb 06 More on data fitting lect09 Lecture Files
Tue Feb 11 Norms of vector and matrices, matrix condition number lect10 Lecture Files
Thu Feb 13 How floating-point works lect11 Lecture Files
Tue Feb 18 Eigenvalues, eigenvectors, graphs, and matrices lect12 Lecture Files
Thu Feb 20 Eigenvalues, eigenvectors, graphs, and matrices lect13 Lecture Files
Tue Feb 25 Ordinary differential equations (ODEs) lect14 Lecture Files
Thu Feb 27 ODEs: algorithms lect15 Lecture Files
Tue Mar 03 ODEs: stiff problems lect16 Lecture Files
Tue Mar 10 Singular value decomposition lect17 Lecture Files
Thu Mar 12 Applications of SVD lect18 Lecture Files

num ready? description assigned due
finalexam true Optional Final Exam  (LaTeX source file) Fri 04/10 11:00AM Tue 04/14 02:00AM
h01 true Some math background  (LaTeX source file) Tue 01/07 09:30AM Mon 01/13 11:55PM
h02 true Matrix manipulation and the temperature problem  (LaTeX source file) Tue 01/14 09:30AM Mon 01/20 11:59PM
h03 true Ax = b  (LaTeX source file) Tue 01/21 09:30AM Mon 01/27 11:55PM
h04 true Temperature matrix, least squares data fitting  (LaTeX source file) Tue 02/04 09:30AM Mon 02/10 11:55PM
h05 true Least squares and floating point  (LaTeX source file) Tue 02/11 09:30AM Mon 02/17 11:55PM
h06 true The power method, sparse matrices, and PageRank  (LaTeX source file) Tue 02/18 09:30AM Wed 02/26 11:59PM
h07 true ODEs  (LaTeX source file) Thu 02/27 09:30AM Wed 03/04 11:59PM
h08 true Laplacian matrices and orbital ODEs  (LaTeX source file) Thu 03/05 09:30AM Wed 03/11 11:59PM

exam date description ready? info
01/30 09:30AM First Midterm true e01
03/05 09:30AM Second Midterm true e02
03/17 08:00AM Final Exam false e03