A real Caltech course, not a watered-down version. This is an introductory course on machine learning that covers the basic theory, algorithms, and applications. Machine learning enables computational systems to adaptively improve their performance with experience accumulated from the observed data. It has become one of the hottest fields of study today, with applications in engineering, science, finance, and commerce. The course balances theory and practice, and covers the mathematical as well as the heuristic aspects. The lectures follow each other in a story-like fashion, with the main topics listed below. Prerequisites: Basic probability, matrices, and calculus
The best Machine Learning class available for free online, period (I also took Coursera/Stanford's). This class will make you understand very well the principles underlying machine learning. You will do some programming assignments as well but the goal of those assignments is for you to understand what you are doing and why you do it (vs implementing some textbook algorithm for the sake of it). It has the right balance theory/practice. Serious students will love it.