At the graduate level I teach the courses Pattern Recognition (EEL 5825; Fall semester), and Introduction to Neural Networks (EEL 6812: Spring semester). In EEL 5825, we cover topics such as Bayesian Classification, Linear Models for Classification, Non-Linear Models for Classification, Clustering Algorithms, Regression Models, and Dimensionality Reduction. In EEL 6812 we cover topics such as History of Neural Networks, Perceptron Neural Networks (SLP and MLP), ART Neural Networks, Radial Basis Function Neural Networks, and Support Vector Machines.