From fish schools to traffic jams, natural and artificial systems alike exhibit forms of collective behavior. In fact, the onset of collective behavior in a system of interacting individuals often corresponds to a period of broader transition in the system from a disordered to ordered state. Why do environments as diverse as the ocean and human society follow the same pattern of emergence? The course takes up this question through an exploration of physical and biological systems, such as insects and animal groups, and human crowds; and case studies in transportation, robotics, and social networks. Students will learn to model, analyze, predict, and even synthesize collective networks of all kinds using quantitative methods such as graph theory, dynamical systems theory, agent-based modeling, and data-driven approaches. No prior knowledge of systems theory or methodology is necessary.