Hybrid systems combine discrete behaviors (such as software or state machines) with continuous behaviors (such as the physical world).  A large number of applications can be viewed in this way including embedded systems, robotics, aerospace systems, process control and biological systems. Autonomous systems like self-driving cars and unmanned drones can also be analyzed using hybrid systems techniques. Models for hybrid systems often use combinations of state-machines and differential equations. The course covers modeling, design, analysis, and verification methods.