This is a course in practical Neural Networks. Though advanced Caltech CS courses provide a theoretical and highly rigorous treatment of machine learning, Practical Neural Networks would be a brief and instructive overview designed for casual programmers less interested in the nuances of the theory who simply want to include neural networks in their programming work. We will go over single and multi-layer, fully-connected perceptrons including simplified error analysis and backpropagation, starting at the most fundamental level. The course will also teach students about industrial and academic applications of neural networks and how to recognize tasks that neural networks are suitable for. Only a rudimentary knowledge of programming is required for this course.