Methods in Computational Science

This textbook provides an introduction to computational science with methods and algorithms for familiarizing readers with the field's theoretical foundations and practical skills. It is suitable for advanced undergraduate and graduate students in computer science and data science, as well as practicing mathematicians, data scientists, computer scientists, and engineers.

Format: Paperback / softback
Length: 395 pages
Publication date: 01 September 2021
Publisher: Society for Industrial & Applied Mathematics,U.S.

Computational methods play a vital role in nearly all scientific disciplines, and it is crucial for scientists and engineers to have a basic understanding of their potential and limitations. This comprehensive textbook aims to introduce computational science by presenting a range of methods and algorithms, with the primary goal of familiarizing readers with the field's theoretical foundations and equipping them with practical skills for utilizing and developing computational techniques.

Methods in Computational Science expands the traditional curriculum by incorporating new topics such as high-performance computing, adjoint methods, machine learning, randomized algorithms, and quantum computing. The book is structured around a set of fundamental algorithms presented in the form of pseudocode, allowing readers to grasp the core concepts easily. Theoretical material is accompanied by numerous examples and exercises to reinforce understanding and application. Additionally, Python implementations of many key algorithms are provided, making the content accessible and practical for computer science and data science students at the advanced undergraduate and graduate levels.

This textbook is well-suited for various courses, including Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory. Its self-contained nature also makes it an excellent resource for continuous learning for practicing mathematicians, data scientists, computer scientists, and engineers in the field of computational science. By mastering these computational methods, readers will be well-equipped to address complex scientific problems and contribute to the advancement of their respective fields.

Weight: 854g
Dimension: 178 x 258 x 28 (mm)
ISBN-13: 9781611976717