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Katie Cornog

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This course covers a lot of material. Although it is advertised as taking 8-10 hours per week, it takes almost everyone closer to 15-20. This course is taught as a Stanford graduate course, and is considered a hard one even at Stanford. To get the most out of the course you should have a fairly good knowledge of probability and statistics. For example, do you know clearly what a marginal distribution is? a conditional distribution? Are you very comfortable with Bayes rule? You should also be comfortable programming in Matlab. There are 9 programming assignments. A structured outline of code is given, but you must be able to understand it an fill in the missing algorithmic parts. The code can be confusing to interpret due to the use of many advanced Matlab features. The programming assignments were the best aspect of the course for me because being guided through an implementation of the techniques makes them much clearer than reading a book or listening to a lecture. There is an active online community for this course. This is helpful for understanding some of the ambiguities in the lectures and homework assignments. I found the textbook, although not required, to be a big help in trying to do the homework. Often topics were only touched on superficially in the lectures and yet the homework questions were very detailed. The book filled in the needed material.