This talk is on the identification of complex dynamical  systems with recurrent  neural networks. The learning of the network parameters is only a subsection of such an effort - even more important is the understanding of the underlying process and its translation into an appropriate network architecture. Thus, not data alone but the interchange with the conceptual thinking is the basis of a successful application. We will see this style of thinking in combination with several real world applications in the talk.