For anyone looking for a GPA boost, look no further than E96C taught by Professor Bill Kaiser. Overall, Professor Kaiser is a really nice, considerate, chill, accommodating professor, but I just feel that this course is so worried about easing freshmen into college (it's designed for freshmen ideally) that there's honestly no workload in this class. You can tell that Kaiser is an expert on sensor tile, not to mention extremely passionate, but I feel that in hindsight, I've learned pretty much nothing about how sensor tile works (writing the code, performing the experiments, etc.). Now, I will attribute part of this down to the fact that I could've been more invested in this class, but I find that the majority of people, including myself, do the bare minimum and walk out with the grade rather than investing more time and truly learning about sensor tile.
In terms of class structure, each week consists of one lab (aka discussion) section and a lecture slot. If your lab section time doesn't fit/work with your schedule, it's okay, since you can show up to any section and sign in on the sign in sheet there. Lectures mostly consist of Professor Kaiser talking about different applications, fields of sensor tile or machine learning, and giving a very layman's lecture on how neural networks with regards to sensor tile works, an idea that is interesting and quite hot at the moment in industry. Talking to Professor Kaiser more in-depth could really give you some valuable insight on this topic (if this is what you're potentially interested in). Participation is supposed to be stressed in this class (part of the grading component), but honestly, many people, including myself, ended up skipping on lecture towards the end of the quarter, as I personally found his lecture presentation a little dry (but others may object to that). Judging from the grading scheme,
I'd wager it's pretty evident that they don't really check for participation (unless you've literally never shown up to a single lab).
During the lab sections, you should have ample time to complete the tutorial, given that you aren't goofing around or wasting time. Kaiser, the TA, and all the student helpers are on hand if you have any questions, and most of the time the code alterations are very similar in nature from tutorial to tutorial. For the final project, Professor Kaiser is extremely considerate. At first, many students struggled with the implementation, but the professor ended up sending a class-wide email telling us exactly how to alter the code (literally) for the baseline project. If you want more experience and delve deeper into sensor tile, you could expand on the baseline project, but talking from past students, many just complete the baseline for the final project. Atmosphere during lab sections is really chill, and it's a great experience (especially if you have a friend to work through the tutorials with).
If I had more time, I probably would've spent more trying to learn more about sensor tile and how the code works, but otherwise, it's one of those classes where you take the grade and move on. Final remarks, there is no textbook, but the IoT kit itself could cost around $120-ish. Try seeing if you can't ask a friend who's taken this class before for theirs, but the Professor also has spare kits for students who "forget to bring theirs", so make use of that how you will.

Such a kind and earnest professor. You can clearly tell that he is passionate about machine learning and teaching it to students. 11/10, would very much take again.

While the professor was extremely nice and concerned about students, the course itself was not very in depth or interesting. The lectures were tedious to get through (and many students starting ditching class as the quarter went on) and during recitation, students were expected to work through tutorials relating to the sensor tiles which honestly didn't teach us much. I didn't really learn much from the class and honestly still don't know what Internet of Things is, but the workload was light (to the point of being almost nonexistent) and pretty much everything got an A. The final project and presentation were also pretty low key.

This class was a bit of a mixed bag near the end, although the professor was very helpful. At times, I had almost no work--the only work I did was in my lab section. Starting with tutorial #9, however (assigned around week 6 or 7 but given a few weeks to work on it), there was a lot more work (tutorial #9 took me about 20 hours, and the final project another 10 on top of that (it builds off tutorial #9)). Professor Kaiser said we did not need coding experience, but I found it *essential* to be able to complete tutorial 9 and the final assignment. (That being said, I think CS31 would suffice.) Still, Professor Kaiser was very helpful with any kind of issues and working together with my group on the final project.

I went to office hours a few times but only the TA was there--according to Professor Kaiser, he has had the same TA for quite some time, so I am not sure if he will be changed for next year. I did not find the TA to be very helpful, as for one of the tutorials he started going on a tangent about how we (myself and the other students there) should know more about sine/audio waves than was stated to be required for the class. He seemed to think these were things we were supposed to learn during the course of the class, but I personally did not. As such, my group ended up doing the tutorial by ourselves instead of getting more help.

Overall, I think the class was just not suited for me because I have very little interest in sensors, but Professor Kaiser was definitely very passionate about the topic and offered us help in getting more involved in sensor/internet of things-based research/projects for after the end of the class. I can't say I would recommend the class unless you are already interested in the topic or wanting a bit of a GPA boost, however, since for me it was pretty boring (although easy). It also requires you buy 2 pieces of hardware and some cables, though, which totaled around $120, so take it at your own risk.

I am actually selling my hardware + cables for the class (STM32 Nucleo-64, SensorTile, 2 cables) for $95 if anyone is interested. Email me at sierrarose@ucla.edu. (11/15/19)

The best...he hooks it up in office hours and is very personable and a good lecturer. He goes out of his way to help you out. He actually helped a bunch of us students like an hour before our final and totally helped, and had no problem with that.

Not a bad class in general...and Kaiser really cares about his students learning. Unfortunately he uses these overheads that help sometimes, but hurt most of the time. For instance, when he's explaining a circuit diagram, it's nicer on the overhead with it's graphics, but when he derives a huge equation, not writing it down honestly hurts our ability to recall it for homework or more importantly the exam. His midterm was cake....but beware, his final was difficult. Very complicated. Take him though, he's good.

Awesome!!!
Best Prof in the whole wide world.

You can learn a lot from this guy. His EE10 class is pretty easy. He gives easy homework problems and the tests aren't bad either. But on top of that, he posts all his lectures on the web. Not only do they have the basic ideas and sample problems, he actually goes in depth about the actual physical circuit elements. Recommended highly for EE 10

Great professor. Makes material that could be potentially hard to understand very clear and concise. Has great notes for all his lectures and is very organized. Professor kaiser displays a genuiene cocern for his students and really tries to make sure that everybody learns the material. Definetely go to office hours because professor kaiser is extremely go at explaining the material and is very friendly.

He is a very good professor. Very concerned with student learning and is always available outside of class for help. He is very organized and the lectures are interesting and easy to follow. I would completely recommend this professor.