ABSTRACT

This textbook is a comprehensive introduction to computational mathematics and scientific computing suitable for undergraduate and postgraduate courses. It presents both practical and theoretical aspects of the subject, as well as advantages and pitfalls of classical numerical methods alongside with computer code and experiments in Python. Each chapter closes with modern applications in physics, engineering, and computer science.

Features:

  • No previous experience in Python is required.
  • Includes simplified computer code for fast-paced learning and transferable skills development.
  • Includes practical problems ideal for project assignments and distance learning.
  • Presents both intuitive and rigorous faces of modern scientific computing.
  • Provides an introduction to neural networks and machine learning.

part I|124 pages

Introduction to Scientific Computing with Python

chapter 21|34 pages

Introduction to Python

chapter 2|50 pages

Matrices and Python

chapter 3|18 pages

Scientific Computing

chapter 4|20 pages

Calculus Facts

part II|256 pages

Introduction to Computational Mathematics

chapter 1265|48 pages

Roots of Equations

chapter 6|72 pages

Interpolation and Approximation

chapter 7|28 pages

Numerical Integration

chapter 9|64 pages

Numerical Linear Algebra

part III|106 pages

Advanced Topics

chapter 38210|34 pages

Best Approximations

chapter 12|20 pages

Eigenvalue Problems