Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings.- Includes tips, warnings and try this features within each chapter to help the reader develop good programming practice- Summaries at the end of each chapter allow for quick access to important information- Includes code in Jupyter notebook format that can be directly run online
PART 1 INTRODUCTION TO PYTHON PROGRAMMING CHAPTER 1 Python Basics CHAPTER 2 Variables and Basic Data Structures CHAPTER 3 Functions CHAPTER 4 Branching Statements CHAPTER 5 Iteration CHAPTER 7 Object-Oriented Programming CHAPTER 8 Complexity CHAPTER 9 Representation of Numbers CHAPTER 10 Errors, Good Programming Practices, and Debugging CHAPTER 11 Reading and Writing Data CHAPTER 12 Visualization and Plotting CHAPTER 13 Parallelize Your Python PART 2 INTRODUCTION TO NUMERICAL METHODS CHAPTER 14 Linear Algebra and Systems of Linear Equations CHAPTER 15 Eigenvalues and Eigenvectors CHAPTER 16 Least Squares Regression CHAPTER 17 Interpolation CHAPTER 18 Taylor Series CHAPTER 19 Root Finding CHAPTER 20 Numerical Differentiation CHAPTER 21 Numerical Integration CHAPTER 22 Ordinary Differential Equations (ODEs) Initial-Value Problems CHAPTER 23 Boundary-Value Problems for Ordinary Differential Equations (ODEs) CHAPTER 24 Fourier Transform
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