All complex systems are made up of interconnected parts. This chapter introduces network science as the study of the relationships between parts. Simple line, ring, tree, grid, and other orderly networks are introduced and contrasted with random networks. Small-world and scale-free networks are explored as lying between ordered and random networks. Throughout, basic network measures such as histograms, clustering, centrality, pathlength, and diameter are introduced as well as the idea of an adjacency matrix. Using these measures, structural redundancy, network phase transitions, nested and overlapping networks, long-tail distributions, and black swan events are all explored. The growth and development of networks is also addressed through the rich-get-richer, L-system, tiling, and pruning algorithms. Examples are drawn from gene networks, ecosystems, language, social networks, chemical reactions in cells, and the formal and informal communication channels within a company. More provocative applications are given for the internet of things and the possible future evolution of humans. The chapter concludes with questions for either reflection or group discussion as well as resources for further exploration.