Scalable analysis and synthesis of robust control systems. Motivation throughout from case studies in tech, neuro, bio, med, and socioeconomic networks. Co-design of sparse and limited (delayed, localized, quantized, saturating, noisy) sensing, communications, computing, and actuation using System Level Synthesis (SLS). Layering, localization, and distributed control. Computational scalability exploiting sparsity and structure. Uncertainty, including noise, disturbances, parametric uncertainty, unmodeled dynamics, and structured uncertainty (LTI/LTV). Tradeoffs, robustness versus efficiency, conservation laws and hard limits in time and frequency domain. Advanced topics, depending on class interest, can include interplay between automation, optimization, control, modeling and system identification, and machine learning, and nonlinear dynamics and sum of squares, global stability, regions of attraction.