We present an introduction to the modeling of networks of nodes which parse the information presented to them into an output. One example is the nodes are excitable neurons which are collected into a nervous system for an animal whether invertebrate or vertebrate. We will focus on the development of the ideas and tools that might help us understand how to build a model of such a system being careful to explain the many approximations or model errors we make along the way. We start with a discussion of low level biophysical concepts such as the cable equation and the Hodgkin - Huxley model and end with graph based models of computation. We also include motivational arguments that show hardware and software issues in neural models are interwined.