We write the introduction to the two-volume Handbook of Computational Social Science with excitement and awe. The handbook brings together a considerable corpus of research and insight, with 22 contributions for volume 1 “Theory, Case Studies, and Ethics” and 22 contributions for volume 2 “Data Science, Statistical Modelling, and Machine Learning Methods.” Over 90 experts contributed from a wide range of academic disciplines and institutions to provide a mosaic of the diversity of computational social science (CSS) scholarship. They lay out the foundation for what CSS is today and where it is heading, outlining key debates in the field, showcasing novel statistical modeling and machine learning methods, and also drawing from specific case studies to demonstrate the opportunities and challenges presented by CSS approaches.