This course provides math background for students of Cognitive Science, Artificial Intelligence, and related fields. The specific math topics studied include probability, linear algebra, and logic. The course presents them in the at the same time that it introduces widely-used tools such as Bayesian networks, simple neural networks, Markov models, logic as a representation language, latent semantic analysis, etc.
The choice of mathematical topics is based on the application areas. The course is unusual because one will learn a lot of mathematics, but in less depth than one would see in classes devoted to the math alone. Goals for the course are to give students a good knowledge of a few topics of importance to current cognitive science, and also the tools to learn the mathematics behind the tools that they will need in their own research.