You will find that the author here is actually a world renown subject matter expert in this field. His book is pretty much the bible on concepts here. And for those talking about the whole "intro" thing, this material is far from "intro" level material. I mean, if you want to think about it in terms of complexity, this is like an "intro" to quantum mechanics and string theory.
You need a very good understanding of probability and statistics, set theory, and strong mathematical skills in order to work out many of the issues. The math involved in partially observable Markov decision processes gets pretty overwhelming without that basis (and that is something on the course curriculum). That said, I am a little disappointed that they do not cover the entire book. I am pretty sure we did, but looking at the curriculum, they added a lot of stuff on games and robotics which I had split as different courses and didn't cover in the intro class (well, I personally had separate courses for "intro to AI", "advanced AI", "neural networks", "robotics", "machine learning", and "game theory" as an undergrad to meet my track requirements, "robotics", "neural networks", "machine learning" and "game theory" were actually all masters levels courses which I took for undergrad credit, as those were a lot more interesting to me than taking some random CS elective, and my adviser and professors signed off on letting me take them).
Now that I think back on it, I remember the during the final in "Advanced AI". I was one of the last people there (maybe 5 people left out of the 30 or so in the course) needing to ask the professor a question about the final question, because his question had no valid answer due to a mistake he made in the initial state of the problem. And after standing there with him for a few minutes going over all my work on the problem he agreed with me as there was no solution, and he then announced a change to the problem. He looked at all the other finals which had already been handed in and told me afterward that all of them made the same mistake he made when he formulated the question. Needless to say I got one of the two A's he handed out that term, and that was when he invited me to take his masters class the next term on "machine learning" since he knew I could handle the material. That all said, I don't think I have used any of that knowledge in my work, but it sure was a lot more interesting than anything else I would have taken, and they didn't seem to have things like crap "busy work" (i.e. something that will take you 30 hours to do that week simply because the professor feels that you need to do 30 hours of work to hand in to him each week...)
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