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Grade distributions are collected using data from the UCLA Registrar’s Office.
Grade distributions are collected using data from the UCLA Registrar’s Office.
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Do not take this Professor at any cost. Nobody could follow anything he's doing and when it came to exam time I was extremely under prepared. the HW is not helpful and the lecture notes are a mess, the TA discussion notes are somehow worse. He doesn't post solutions for his exams so you won't have the option to review what you did wrong on the midterm while preparing for the final. I alway fall asleep during his lectures, yes they are that boring and it's all theory. There is an extra credit project that im unsure as to how much its worth but that too doesn't depend on your knowledge from this class but rather your knowledge on Python and machine learning.
Extremely overrated professor. I don't know how he is for 131A, but for 132A, all he does is mumble, scribble on the board, and make mistakes. He offers no applicable real life examples and insists in indulging in the pure mathematical theory.
His grading scale is also WAY overblown, he is not a generous grader at all...
All in all, if you are an EE student who likes think in terms of practicality, forget Lorenzelli.
Go for Villasenor, I hear he accompanies the theory with application.
This class was not as bad as some other reviews claimed, since everything could be learned if people don't mind self-studying for a bit. For my quarter, approximately 30% of students got A's, which was not bad either. However, it did seem like the extra credit project he offered was a trick to lure students in giving him better evaluations, since I am certain much more students would get an A with a 15% extra credit applied after the curve (just like he claimed). The workload was really reasonable, and the project was pretty short, so I wouldn't complain too much about it. Overall, I feel neutral about this class and this professor, and I wouldn't mind taking this class again with him.
This has to be one of the worst classes I ever taken at UCLA. The professor is really nice and funny at times, but the way he goes over material in class is awful. I didn't pass the class but I believe that most of the blame should be put on the professor for not being able to clearly go over content. He has the tendency to go over things out of topic and it results in him and/or his students getting loss and confused. He would speed through his teaching and writing on the board, making it a task to keep up and understand what he's trying to teach. The grade distribution shown on here and the positive comments don't reflect how bad of a quarter it was for Winter 2023. I recommend you all to avoid this professor by all means.
As a supplement to previous comments, even solution manuals for the homework themselves can contain a lot of errors, so if you think your approaches are correct, then it is very likely that they are correct indeed, so remember to mention these possible errors in the office hours/discussions. The textbook helps as others say, and you can solve relevant problems at the end of the chapter, which is helpful. My strategy is to give up the final project and spend all my time doing practice problems and reviewing relevant chapters of the textbook, and it works for me. The average midterm score was a mere 31.36/50, the median was 32.0/50, and the standard deviation was 9.82. The final average score was 68.69, the median was 70.5, and the standard deviation was 15.63. I got 46.75 in the midterm and 92 in the final, so it is possible to get a top grade without extra credits, but you need to substitute that project time before the final for regular reviews throughout the quarter. Still, you may not be able to clearly connect different topics until you do the final review.
Supplement: The first 2 weeks can be the toughest period of the course, and I spent a lot of time figuring out those Hilbert transform kinds of stuff and reviewing certain concepts from ECE102. The Matlab questions are usually about the simulation of different modulation schemes, so you can sometimes copy and paste part of the codes from your previous homework. Although he recorded lectures, the videos had poor quality and were nearly indiscernible. If you are interested in data science, I would like to say there is a weak connection between this course and DS, as you will briefly learn concepts like maximum likelihood and decision boundaries.
Lorenzelli is a bad lecturer. Given this though, his tests are doable if you read the book (I assume a lot of people chose not to read the book rigorously and rely only off his lectures, that's why our midterm and final averages were 30/50 and 68/100). His lectures, otherwise, are meaningless and there is no real point in going to class, unless to ask questions. He's pretty nice and patient during office hours so you can ask away at questions there. EE 113 was not really relevant to this class (the only time you might ever need it is for MATLAB homeworks, but that's it), and we focused almost entirely in continuous time domain. Make sure your probability is up to speed, because this class is heavy on probability.
You may not be able to avoid Lorenzelli if you ever need to take 132A. So far for the past few years its only been offered every winter quarter, and he is the only person to teach it for winter. Diggavi teaches it in Spring, but I have heard horror stories about Diggavi's 132A, and has worse grade distributions compared to Lorenzelli I believe. This class is generally not well formatted to begin with, since they have to cram so much content in so little time. However, the tests are designed such that cramming and self-studying the book should assure you a decent grade. The TA does a review session for the final, where some of the questions are almost carbon copied onto the actual final, although I think this was specific to our year since the class at large did so bad on the midterm.
If you need to pick 132A as one of your 6 choose 8, I'd say go for it, but be prepared to do quite a bit of reading (although even then its not bad; if you set aside 2-3 days in total, you can cram all the chapters Lorenzelli tells you to refer to).
Also, on the extra credit project (team project, 3 people): for our quarter, he made it on a MATLAB OFDM communications topic. The spec gives you a few guidelines but otherwise is open-ended, and you can net almost 10% on top of your overall grade (however, Lorenzelli was mum about whether this is applied pre-curve or post-curve). However, it seems he is very picky about his grading, as he mentioned if we did the project incorrectly, even if we had worked or showed a decent attempt, no points would be given, so that's where I think criticism from others comes from. In my team however, we got ~7 extra credit points, and one of our members who did well on the midterm, but not the final, still got an A, indicating there was indeed still a curve of around ~20% on top the straight scale (I'm not sure if Lorenzelli curves before or after accounting for extra credit). Keep this in mind if you choose to do it.
I can definitely say this was the worst class that I've ever taken in my life. The class wasn't organized at all, and all my friends were just studying by themselves. There is a Matlab problem in the HW, which takes a lot of time especially if you're not familiar with it.
The midterm average was around 30 / 50, and the final average was 68 / 100. I got 25 on the midterm and 82 on the final. I also did extra credit project which took like a whole day during the just before the final week. Then, I ended up getting B-.
The grade distribution was quite shocking. Even people who get higher than the average on both exams (3 points-mid, 10 points-final higher than average) got B.
If I have a chance, I would NEVER EVER take this class again.
This class was a pain and this prof didn't help to relive that. The lectures are quite dry and boring, but prof is able to explain the concepts somewhat well. You just need to really pay attention and think about it, but that's nearly impossible IMO. I highly recommend reading the textbook bc you'll receive some idea on what's going on. The homework is pretty hard and confusing so you'll need to spend quite some time to understand or have someone help you out. The midterm and final are quite difficult as well and most of the class doesn't do well for either. One good thing that prof has is a extra credit project where you use the machine learning library in PyTorch for a communications related project. It wasn't that particularly difficult as most of the code was given. Overall, the material in general is difficult, but quite amazing when you start to get some idea on how communication systems work.
It will forever elude me why the department insists on having Lorenzelli teach every class having to do with signals and systems. This is my 3rd time being forced to take a class with him and just like the last two times, it was dogshit. He is extremely unclear in his lectures and you will not be able to learn anything conceptually or application-wise. He is all about deriving equations you never use from rigorous mathematical theory and never stopping to annotate or explain what anything means. This is a class where I spent the majority of my time just trying to understand the solutions manual to the homework.
Excellent professor. His lectures are very easy to follow and he definately knows his stuff. He is brilliant yet modest and I think he was definately one of my favorite professors at UCLA, for his knowledge, approachability, and yes, he is very nice. He could have given me an F and I'd still have no negative opinions of him.