I'm so glad Professor Darwiche decided to become a Professor. I just wish he taught more CS classes; I would take them all. He is kind, patient, clear, and knowledgeable. I learned a tremedous amount in his class (and not just retaining the information long enough to get a decent grade).
Make every effort to take his class, even if you're not interested very much in AI. I can't remmeber one lecture where the classroom wasn't packed. If you're a CS major, you know how rare that is. He's just that good.

Adnan is one of the best professors at UCLA. Really, this man makes me feel proud of being a UCLA student. For once after 3 years I don't look at Youtube videos of other universities and feel that I'm missing out a lot by not going to MIT or Stanford.
I wish this class would continue on to AI 2 and AI 3 as a whole year program. Adnan should basically teach anything remotely related to AI and algorithms. He simply breaks down everything to conceptual understanding of the material rather than regurgitating some mathematical notation and call it a day.

This class was a lot of fun for me. You have to still work pretty hard for an A but the exam and assignments are fair.
His enthusiasm for teaching the subject and his energy during the lecture is contagious. It's really hard to fall asleep during his lecture.

I highly recommend this professor.

Professor Darwiche is great! He's an engaging professor and the projects are interesting and fun. His tests are also fair and he makes an effort to make sure the material is understandable. The course covers a broad range of AI topics and gives a good overview of the field.

TL;DR Class is very slow paced. I wish there would have been more of the interesting material and less alphabet soup and symbols to memorize.

First few lectures are on Lisp, which is very easy, but also pretty much immaterial to the actual meat of the class (nothing you do in lisp couldn't be done EASILY in the other languages we learn as CS majors). I'm guessing they do it this way so grading is easier since the class is relatively popular. Also, they limit how much of the language you are allowed to use in the projects which is odd.

The next part is on Search and 2 player games, but the interesting part of Search (A*) was unsatisfyingly short for me. For 2 player games, you really only learn the simplest version Alpha-beta (and do no projects on it), which is a highly shortened treatment of a very interesting subject in my opinion.
You then cover SAT-Solving, which was interesting, but the project was just an N-Queens in Lisp which reduced to basically just translating a loop, and didn't require any of the techniques previously described in the class except depth first search ($10 says a solution that just returns precomputed solutions for the first 50ish problems would get full credit).
The last part of the class is Bayesian networks, which was probably given too high level a treatment. The problems we had to solve with it we were given software for, so I don't feel this was effective for teaching me.

You might think that given what I've said above, that I didn't like this class. That isn't quite true. I overall enjoyed it, but I feel it could have been a lot more.

Adnan, if you see this, here are my suggestions.
1.) Open up the allowed language list. It will make grading trickier, but will also let you spend more time on important material.
2.) Spend more time on A* and SAT and less time on the "dumb search" techniques (BFS etc)
3.) Spend more time on "game AI". Alpha-beta is one algorithm, but Monte Carlo Search with Upper Confidence Bound is a another one that is very interesting (popularized in 2006! and performs much better than Alpha-beta for certain games). I'm of course not an expert in this field, but there's a lot of interesting things that could be explored here
4.) Go a little deeper on Neural networks and the algorithms they use. It was too high level to be useful to me in my opinion. Consider having us implement one of the algorithms instead of just trying to figure out the SamIAm gui for a project.

I know AI has a large breadth as well as depth, but I still find the lack of depth in this class disappointing.

He is an excellent prof and cares a lot about his students.
The TA Summing Chen was awesome too.
He actually answers questions in class and does not rush even if he is falling behind.
The projects were awesome(and hard). I struggled but if you are into AI you would love them.

Its just an intro to AI class so expect a little of theory and less programming.

All in all it was a value class from a great prof. Had to put in time, hw's and final were hard. Ended up with an A- after working really hard. I would recommend him :)