Python Programming and Numerical Methods

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

Qingkai Kong is an Assistant Data Science Researcher at the Berkeley Division of Data Sciences and Berkeley Seismology Lab. He has a Master's degree in Structural Engineering and a PhD. in Earth Science. He is actively working on applying data science/machine learning to Earth science and engineering, especially using Python language.