The course offers a top level view on the area of optimization. The part on unconstrained continuous optimization covers iterative methods ranging from steepest descent to trust region methods The part on constrained continuous optimization covers concepts like duality, convexity, and Lagrange approaches. The part on discrete optimization covers intractability and approaches to NP-hard problems (approximation algorithms).