I thought this class was very well done! Professor van Den Broeck does an excellent job of explaining the material in an easy to understand way. At the end of the class I thought I had a good introduction to different aspects of AI. The homework and exams were also very fair and very doable. Overall I would definitely recommend this course, I learned a lot and it definitely wasn't a huge amount of work.

Overall this class was pretty average. Not bad but not good either. I'd still probably take it again but if I had other interesting classes available I'd probably opt for those instead.
In the pro category, Guy is a pretty decent lecturer. He does a good job of going over the points, explaining it clearly, and making sure the class gets it. Only thing I didn't like is he mixes powerpoint slides with drawing on the board, so as someone who likes to just refer to online notes it's a bit of a pain. Also I thought the tests were fine. The midterm was just problems that were covered in homeworks or class. The final was multiple choice, and although I understand the point a lot of the other reviews made here, I thought generally the questions were ok. They mostly wanted you to think critically about the concepts rather than just memorize them all. Also generally speaking the homeworks don't take that long to do, so this wasn't as time consuming as some other CS classes can be.
On the con side, the class is poorly organized, and at least for this quarter I thought the TAs were not good. I stopped going to discussion because my TA seemed to mostly confuse people or not know what they were talking about. They are also pretty poor at responding to stuff like homework questions, scheduling the release and deadlines for the homeworks, grading in a timely fashion, etc. And for the midterm they made you go to a specific TA's office hours to get regrades for each question, so essentially everyone had to go to 3 separate office hours. And in my opinion they graded poorly and would take away points for arbitrary reasons.

He is a nice guy and care about students' learning, but his lectures are not very clear. In fact, this is one of a few classes that I think are on par with Eggert's CS 33. It is very hard to follow sometimes and I have no idea what's important to write down. Basically, If you don't spend time reading that textbook, you will probably have trouble understanding concepts.

The first two homework are too easy (Lisp coding that can be finished in 10 minutes), and the last two are a disaster.
Homework 3 as far as I know no one received 100. Basically after spending several hours optimizing routines and heuristics will give you a score of 94.2 instead of 94.
Homework 5 and 6 are like math questions. They are pretty good, and they really help me understand what resolution, markov assumption, etc. are. However, solutions are never posted, and we pretty much have no idea what's going on after we submit our homework. Due to students' constant requests, the TA inputted what questions we did wrong and how much points were taken off like near 12am of the final exam. But, I can't comment on how helpful they turn out to be.

The final exam is all multiple choices. It is very anti-south campus. If you are good at memorizing stuff, you can get 90+ for not understanding any math, logic or coding; If you are not good at it, like me, you are most likely screwed.

In the end, I am pretty frustrated with this course. This AI course seems too traditional. It focuses too much on search (why not talk about it in 180?) and logic (not everyone has taken Philosophy 31), and talks too little about current learning algorithms. Homework and exams are probably reused so solutions are never posted, which means if you did something wrong, you will probably be still confused about why you did it wrong after the class is over. In the end, I can safely say I hardly learned anything after struggling through the whole quarter. As a reference, I have a 4.0 GPA for all CS classes before this quarter.

Overall the class was pretty good. The lectures were entertaining and the homework assigned wasn't too bad. However, the final was supposedly concept-based, but had a lot of definition/memorization based questions.

Not sure why there are some bad reviews, but for the online version, I thought it was pretty good. Everything was prerecorded so every lecture was very efficient and easy to follow. The homeworks aren't too stressful either. Nothing on the midterm or final that was unfair or not taught -- it was very reasonable. Definitely recommend taking it with this prof.

Professor Van Den Broeck clearly has a good understanding of how to teach the course material. The lectures are well structured and while some sort of annotated slides (or lecture recordings) would have been nice, the textbook and slides combo worked fairly well when I needed to catch up on missed lectures (and previous year recordings are also available I believe). The one weakness of this course I feel is the disconnect between the lecture contents and the homeworks. Professor makes it very clear from the start that he has little to no involvement in the creation and grading of the homework assignments, and that the one TA that is in charge of them should be contacted for all related inquiries.

This is all well and good except for the fact that the TA in charge of grading was seemingly asleep at the wheel the entire quarter. Multiple times on piazza the TA (who I believe does not have any discussion sections and just does the homework?) said that any homework grading related questions should be emailed to them, yet despite attempting to contact them multiple times through multiple channels I was never able to reach them regarding points I missed on the first homework (of which I am still at this point in week 10 trying to contact them over). Moreover, aspects of the homework assignments just seemingly outright contradicted what we were taught in lecture at times? For example, professor made a big deal about how our algorithms should prioritize memory usage over execution time, yet our second homework in large part was graded based on how our algorithms performed (in terms of execution time) relative to the other student's submissions. And no, the grading methodology was never explained to us, before or after that assignment was due.

Still, this class was very interesting, was taught by an engaged professor, and while the grading and philosophy behind the homework assignments was unclear, they were all still enjoyable and generally struck a good balance of difficulty level.

This was overall a very average class and average professor.
Professor Broeck, in my opinion, is not the most engaging speaker and doesn't seem all that motivated either. There were multiple instances where he would end class 30-60 minutes early, leaving me and my fellow peers more confused rather than happy. However, he uploaded all of the recordings of his past online lectures which were actually very good and informative. Once I stopped showing up to lecture and strictly watched his recordings, the class started to get a lot more interesting. I guess he's just not the best live speaker, which isn't his fault. He also likes to write on the chalkboard and it's near impossible to read what he writes if you're not sitting in the first 3 rows. So unless you insist on going to in person lectures, I would suggest just watching the recordings, as they're actually pretty good and teaches the material a lot better than live lecture.

The projects are written in Lisp, which as anyone can tell, is a severely outdated language and is frankly a bit pointless to learn. The projects themselves, save one, are pretty easy overall and if we were able to write in a more modern language, they would probably take less than an hour to do. I found myself spending more time trying to figure out the syntax of Lisp than the actual logic itself. Overall, I treated the assignments as more of a functional programming/basic algorithms practice as opposed to new learning, as it just feels like review of CS32 and CS180.

The tests are a whole different beast. The midterm was doable. It felt like a normal CS exam with short answers, input/output problems, coding problems, multiple choice, etc. If you watch the lectures and study the algorithms up to that point, you should do fine on it.
The final however lived up to its reputation. 60ish questions of just pure nonsense. 45 of the questions were True and False, with every 15 questions or so increasing in weight. (ie the first 15 questions are 1 point each, the next 15 are 2 points each, etc). The remaining questions were all multiple choice. I would estimate that if you knew from top to bottom, everything on the lectures and projects, you could probably get around 75% of the final exam. The rest, you kind of have to be lucky and had seen that word or phrase before, or be a good guesser.

Overall, I actually enjoyed the class. Just treat it as a functional programming/algorithms review and enjoy one of the lighter CS classes at UCLA. Don't expect to learn too much new content, as most of the stuff in this class is severely outdated.

Professor Van Den Broeck clearly has a good understanding of how to teach the course material. The lectures are well structured and while some sort of annotated slides (or lecture recordings) would have been nice, the textbook and slides combo worked fairly well when I needed to catch up on missed lectures (and previous year recordings are also available I believe). The one weakness of this course I feel is the disconnect between the lecture contents and the homeworks. Professor makes it very clear from the start that he has little to no involvement in the creation and grading of the homework assignments, and that the one TA that is in charge of them should be contacted for all related inquiries.

This is all well and good except for the fact that the TA in charge of grading was seemingly asleep at the wheel the entire quarter. Multiple times on piazza the TA (who I believe does not have any discussion sections and just does the homework?) said that any homework grading related questions should be emailed to them, yet despite attempting to contact them multiple times through multiple channels I was never able to reach them regarding points I missed on the first homework (of which I am still at this point in week 10 trying to contact them over). Moreover, aspects of the homework assignments just seemingly outright contradicted what we were taught in lecture at times? For example, professor made a big deal about how our algorithms should prioritize memory usage over execution time, yet our second homework in large part was graded based on how our algorithms performed (in terms of execution time) relative to the other student's submissions. And no, the grading methodology was never explained to us, before or after that assignment was due.

Still, this class was very interesting, was taught by an engaged professor, and while the grading and philosophy behind the homework assignments was unclear, they were all still enjoyable and generally struck a good balance of difficulty level.

I thought this class was solid overall, though a part of this is me finding the subject matter interesting. In terms of lectures, I thought Prof. Van den Broeck was did a good job presenting the material. Me having a nodding-off-during-lectures problem aside (not anything to do with the lectures, Boelter 3400 + 3-5 PM just happens to be a really bad combo for me), I thought the lectures were quite clear overall, and I personally found the examples pretty helpful. The professor also posted slides + past lecture recordings of the entire course; I didn't personally use them too much, but I did find the recordings occasionally useful in review, and the content covered is more-or-less the same as the in-person lectures.

As far as homework goes, the best way to describe it is that there...mostly wasn't any? We had 4 homeworks, but only the last one was much work (IMO), and that wasn't even assigned until week 9. The first 3 homeworks involved implementing algorithms in Python, but the assignments were scaffolded pretty extensively and didn't take me more than 2 hours each to do. (That's probably somewhat on the lower end time-wise, but we were given 2 weeks to do each of them.) There were also some questions on course content, but they were pretty much just asking about things covered in lecture. The fourth homework was quite a bit longer and pretty noticeably tougher, but up to that point, for the entirety of weeks 1-8, I probably spent at most 6 hours *total* on this class beyond attending lectures + studying for the midterm. A minor nitpick, grading was really slow, to the point that we basically had no grades for 2/3 of the course (HW1, due week 3, wasn't graded until week 7); fortunately, it wasn't a big deal since the affected homeworks ended up with pretty high averages, but we were pretty much in the dark before then.

As far as exams go, they were somewhat long, and fairly memorization-heavy (moreso the final). Format-wise, our midterm was mostly free response with a few True/False questions, whereas our final was entirely Scantron multiple choice. Prof. Van den Broeck wrote "study guidelines" that pretty much laid out ~75% of both the midterm and the final, and for both exams I think just remembering things said in lecture would get you another 15%; the last 10%, however, usually required a good understanding of the algorithms + a decent amount of thinking (assuming you weren't just guessing, which you could've - multiple choice is multiple choice). The exam room was probably 3/4 empty by the end of the midterm, and the final was only ~60-something? questions in 3 hours, so time wasn't a major issue. The averages weren't exactly high, mid 70s for both; that being said, I think there was a fairly generous curve. I had a ~94% raw score and got an A+.