Numerical relativity has emerged as the key tool to model gravitational waves - recently detected for the first time - that are emitted when black holes or neutron stars collide. This book provides a pedagogical, accessible, and concise introduction to the subject. Relying heavily on analogies with Newtonian gravity, scalar fields and electromagnetic fields, it introduces key concepts of numerical relativity in a context familiar to readers without prior expertise in general relativity. Readers can explore these concepts by working through numerous exercises, and can see them 'in action' by experimenting with the accompanying Python sample codes, and so develop familiarity with many techniques commonly employed by publicly available numerical relativity codes. This is an attractive, student-friendly resource for short courses on numerical relativity, as well as providing supplementary reading for courses on general relativity and computational physics. Includes numerous exercises, and answers to selected problems, allowing the reader to explore new concepts in depth, often through analytical examples that illustrate key features of numerical relativity Provides Python scripts exemplifying two types of simulations often encountered in numerical relativity, so that readers can perform 'hands-on' computational experiments with some of the new concepts Summary boxes highlighting key results, serving as easy-to-find references to important features Several appendices provide the reader with additional background information, as well as a summary of important general relativity tools and equations