Steve Chapra is the Emeritus Professor and Emeritus Berger Chair in the Civil and Environmental Engineering Department at Tufts University. His other books include Surface Water-Quality Modeling, Numerical Methods for Engineers, and Applied Numerical Methods with Python. Dr. Chapra received engineering degrees from Manhattan College and the University of Michigan. Before joining Tufts, he worked for the U.S. Environmental Protection Agency and the National Oceanic and Atmospheric Administration, and taught at Texas A&M University, the University of Colorado, and Imperial College London. His general research interests focus on surface water-quality modeling and advanced computer applications in environmental engineering. He is a Fellow and Life Member of the American Society of Civil Engineering (ASCE) and has received many awards for his scholarly and academic contributions, including the Rudolph Hering Medal (ASCE) for his research, and the Meriam-Wiley Distinguished Author Award (American Society for Engineering Education). He has also been recognized as an outstanding teacher and advisor among the engineering faculties at Texas A&M University, the University of Colorado, and Tufts University. As a strong proponent of continuing education, he has also taught over 90 workshops for professionals on numerical methods, computer programming, and environmental modeling.Beyond his professional interests, he enjoys art, music (especially classical music, jazz, and bluegrass), and reading history. Despite unfounded rumors to the contrary, he never has, and never will, voluntarily bungee jump or sky dive.

1 Mathematical Modeling, Numerical Methods, and Problem Solving
2 MATLAB Fundamentals
3 Programming with MATLAB
4 Roundoff and Truncation Errors
5 Roots: Bracketing Methods
6 Roots: Open Methods
7 Optimization
8 Linear Algebraic Equations and Matrices
9 Gauss Elimination
10 LU Factorization
11 Matrix Inverse and Condition
12 Iterative Methods
13 Eigenvalues
14 Linear Regression
15 General Linear Least-Squares and Nonlinear Regression
16 Fourier Analysis
17 Polynomial Interpolation
18 Splines and Piecewise Interpolation
19 Numerical Integration Formulas
20 Numerical Integration of Functions
21 Numerical Differentiation
22 Initial-Value Problems
23 Adaptive Methods and Stiff Systems
24 Boundary-Value Problems

Appendix A: Matplotlib
Appendix B: Cubic Spline Smoothing
Appendix C: Python Built-in Keywords: Functions, Methods, Operators, Types
Appendix D: Python Functions and Scripts Presented in the Text
Bibliography
Index
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