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.

Easy A with very light workload. Take it if you want a GPA boost. My only complaint is that the edukit was super expensive, I'm selling mine right now. Message ********** if you're interested :)

Here to boost his ratings. A must-take class for the new excited engineering students. You'll learn the skill people regret not learning for 4 years. IoT is a fun class with no workload and an engaging group project at the end. For the first 6 weeks, you learn how to use the STM32Cube IDE. Then you partner with a classmate to make a project in the remaining weeks. For the final project, you need to make a 3-5 minutes YouTube video and a small powerpoint presentation. Trust me it takes maximum 10-12 hours to complete the entire thing. If you are in CE, this is a requirement but if you are CS or EE and wish to learn something new, you can always count on this for teaching something new and also boosting your grades.

This class was required for my major (computer engineering) so I didn't necessarily want to take it, and I'm taking it as a 4th year. However, I am very glad I took it, because Professor Kaiser was one of the nicest, most caring teachers I've ever had at UCLA after 4 years. For freshmen who are looking to take this class: it's a great investment of your time, and you will learn so much useful knowledge about coding, systems, and engineering in general. This will undoubtedly be a great foundation for any engineering curriculum in the area of CompE/EE/CS. It's not a very difficult class either, and won't take up more than two hours out of each week during the quarter. He even designs the class so that, as an outcome, you have a tangible project that you can talk about in interviews. I wish I had taken this class when I was a freshman. 10/10!

Extremely easy class, 1-2 hours of work per week which can easily be done during lab times. The project is very simple and built up very slowly across the ten weeks, but still can come out to be a very nice resume project with the right idea. Professor Kaiser is extremely kind and accommodating, and make sure to use the class to network with other engineers in your field or the upperclassmen class aides!

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 *************. (11/15/19)

This class is a great introduction for anyone going into the field of engineering. Professor Kaiser covers a lot of topics that are going to be the next challenges of the engineering field, and I think he really met his goal about getting students excited about engineering. Professor Kaiser is clearly passionate about the subject he teaches and really wants his students to be too. If you are having problems, Professor Kaiser is very helpful and accommodating, and his TA, Xu, is also very helpful. One time, when my computer crashed, and I had to start from scratch, Xu worked with me over the weekend via email to help me get caught up. Overall, I would highly recommend this class, as the lectures are very interesting, and you learn a lot with the sensor tile.

As a bioengineering major, I found this class interesting. It provides a sneak peek into sensor systems programming, Professor Kaiser's lectures are interesting, but have nothing to do with the tutorials designed to be completed in the lab. Unfortunately, many people don't attend his lectures. Professor Kaiser himself is a very helpful and kind man and him and his TA go out of their way to help you.