Professor
William Kaiser
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Most Helpful Review
Fall 2019 - 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.
Fall 2019 - 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.
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Most Helpful Review
Fall 2023 - The lectures had nothing to do with the assignments. Don't stress at all if you have no idea what's going on during lectures; they covered content which, in my opinion, was too advanced to being taught to incoming freshmen (stuff that you'll learn in upper div EE courses). The assignments are super easy. Just make sure to show up to lectures and lab. Each lecture and each lab make up 1% of your total grade, so if you skip them, it adds up quick.
Fall 2023 - The lectures had nothing to do with the assignments. Don't stress at all if you have no idea what's going on during lectures; they covered content which, in my opinion, was too advanced to being taught to incoming freshmen (stuff that you'll learn in upper div EE courses). The assignments are super easy. Just make sure to show up to lectures and lab. Each lecture and each lab make up 1% of your total grade, so if you skip them, it adds up quick.
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