Further, Daphne Koller is a serious force in the field, and seems to be a pretty good supervisor, so I'm guessing/hoping she is an interesting/engaging lecturer as well. Though, Stanford CS/Stats students are more able to comment on this last point.
[1] http://www.mrc-bsu.cam.ac.uk/bugs/winbugs/contents.shtml
What's the source? She's a brilliant researcher, but I've heard quite the opposite about her attitude towards human relationships...
Working with her was one of the highlights of my undergrad education, and her class was great, too.
"This class does require some abstract thinking and mathematical skills. However, it is designed to require fairly little background, and a motivated student can pick up the background material as the concepts are introduced. We hope that, using our new learning platform, it should be possible for everyone to understand all of the core material."
and "For additional depth, you can refer to the best-selling textbook, _Probabilistic Graphical Models: Principles and Techniques_ by Daphne and Nir Friedman."
I thought about buying the book but thought that listening to the lectures and doing the assignments would be more fun.
A much more cohesive introduction would be Michael Jordan's book draft that has been floating around for nearly a decade now. You can find some of the older versions online, e.g. http://www.cs.cmu.edu/~lebanon/pub/book
Go directly to chapter 5 to see how the language of PGMs can help to clarify a lot of standard material in stats and ML.
> Just good design.