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.



No previous experience in Python is required



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