Python Programming and Numerical Methods: A Guide for Engineers and Scientists

Python Programming and Numerical Methods: A Guide for Engineers and Scientists

Bayen, Alexandre
Kong, Qingkai
Siauw, Timmy

72,75 €(IVA inc.)

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 to allow the students to quickly apply results in practical settings.SPECIFIC PUBLICITY AND CHANNEL OPPORTUNITIESNotes for completion Focused publicity or channel marketing opportunities specific to this project or cluster. Can be left empty if nothing new to highlight.PRIOR EDITION SALES HISTORYn/a Tips, warnings, and try this features within each chapter help the reader develop good programming practicesChapter summaries, key terms, and functions and operators lists at the end of each chapter allow for quick access to important informationAt least three different types of end of chapter exercises - thinking, writing, and coding - let you assess your understanding and practice what you've learnedAll of the code in the book is in Jupyter notebook format that can run directly online INDICE: Part 1: Introduction to Programming for Engineers 1. Modules 2. Variables and Basic Data Structures 3. Functions 4. Branching Statements 5. Iteration 6. Recursion 7. Objects and Classes 8. Complexity 9. Representation of Numbers 10. Errors, Good Programming Practices, and Debugging 11. Reading and Writing Data 12. Visualization and Plotting 13 Parallel your Python Part 2: Introduction to Numerical Methods 14. Linear Algebra and Systems of Linear Equations 15. Least Squares Regression 16. Interpolation 17. Series 18. Root Finding 19. Numerical Differentiation 20. Numerical Integration 21. Ordinary Differential Equations (ODEs) Appendix A. Setup Python Environment. Manage Packages. Virtual Environment B. Version control with Git

  • ISBN: 978-0-12-819549-9
  • Editorial: Academic Press
  • Encuadernacion: Rústica
  • Páginas: 400
  • Fecha Publicación: 01/12/2020
  • Nº Volúmenes: 1
  • Idioma: Inglés