This class at UCLA has been an extremely disappointing experience, ranking among the worst courses I have taken. Dr. Meyer and his head TA, Michael Bogumil, make for a disastrous combination. Firstly, Dr. Meyer's approach to teaching is lacking. Instead of lecturing, he relies on student presentations while only making class announcements. Inconsistencies arose, as attendance was initially disregarded but later enforced in week 8, without any mention in the syllabus. It felt as if Dr. Meyer was merely a placeholder, oblivious to the chaos unfolding in the lab sections due to the incompetence of his head TA. The lab sessions were consistently plagued with issues. Our cell cultures were never ready on time, resulting in incomplete experiments and confusion about the lab sequence. Michael's inability to seed the cells promptly meant our experiments suffered from inadequate cell densities. When I approached my TA about this, she acknowledged the negative impact but stated that it was expected at this point, leaving us to anticipate mistakes from our TAs, which is unacceptable. Changes to the protocols were frequently made without consulting us, leaving us feeling powerless. When I raised these concerns with Dr. Meyer, he seemed genuinely surprised by the last-minute changes. Furthermore, the grading of assignments and tests was abysmal. Reports lacked a clear rubric, and receiving feedback was a struggle, with minimal comments provided. Completing the reports was a time-consuming task, given the excessive number of questions and required observations. The exams were a nightmare, bearing little resemblance to the course material that was never properly taught by Dr. Meyer. The questions demanded specific answers that could only be known if one had seen the test beforehand. The grading process was the most frustrating aspect, as my initial score of 46/75 dramatically increased to 67/75 after pleading for a recount. Such discrepancies should not be tolerated. Dr. Meyer's lack of organization is evident, and it would benefit him to experience this class anonymously, gaining a firsthand understanding of the challenges we endure. Unfortunately, his head TA has yet to take responsibility, severely hindering the students' educational experience.

As with most labs, the whether you enjoy this class or not depends on the TA that you have. Dr. Meyer is very fair with fairly easy tests that are not cumulative, and cover lecture material. He holds review sessions and explains what to study. The class is a bit scattered and felt like we were just learning the surface level of many complex topics. Like, I felt like when we learned about linear regression and standard deviation, as well as stress-strain, the questions had the opportunity to be really hard, but they always ended up being fairly straightforward. Lecture is often boring and feels like it should only be an hour long, but the labs themselves are enjoyable and often get out early. Report guidelines are almost never clear, but graded generously so its ok. Also, be sure to start the lab reports early. There are only 3 over the span of 12 labs, so you think you can start it the night before but they often take around 8 hours or so, so I recommend starting it at least one day early, probably two.

Logistics:
About 10 quizzes (two attempts, takes the average)
6 Lab assignments
1 Midterm
1 final project (can be solo or in group)
Participation grade

This class is very interesting and also very useful however it is very poorly organized. Professor Meyer is very sweet and always tries to help you (especially via Slack) however this class is very confusing and the Labs/HWs are very disconnected from the lecture. He also doesn't provide the best examples for the topics covered and can't break down bigger concepts into smaller ones. I personally thought the TAs did a much better job at explaining and breaking down the concepts. It also helps a lot if you have taken a stat class before.

Although this class isn't a coding class, coding in Python is a big part of this class and I struggled a lot with implementing different Machine Learning models just because I had never seen how to implement one, in addition the questions are very confusingly worded and you have no idea what the question wants you to do. Make sure to attend EVERY SINGLE OFFICE HOUR, every minute you go to the office hour is an hour you save being confused on the labs. The TAs and professor are very helpful in clarifying what the question wants and helping you with the coding aspect. Discussions are helpful but the TAs just don't have enough time to cover lecture material and help with Labs. It would have been much more beneficial if this class was broken into a lecture and a lab portion.

The midterm isn't too bad as long as you do all the previous midterms and get used to his style of asking questions as he generally asks the same types of questions every year.

Overall this class isn't difficult topic-wise but extremely time-consuming just because of how confusing everything is so make sure to leave enough time.

Professor Meyer is one of the best professors I've had at UCLA. The class format during COVID is much different than normal, so I don't think my review will be very applicable for future classes. In short though, this is a class where you truly can learn a lot about how to be a bioengineering researcher if you put the appropriate effort into it, and I am assuming that advice will translate over to this class being in-person again soon.

This class is incredibly useful if you are interested in research, but also incredibly frustrating because of the homeworks.

The class follows a structure where a statistical concept or model will be introduced in lecture and then you will implement that model using python in the following week's homework. The implementation of the model is based on a bioengineering paper, so if the authors did linear regression, then you will perform the same linear regression with the author's data. In theory, this is a great way to show how statistics is used in research and teaches you exactly how you might come to a certain conclusion with data you collected. But in practice the homework questions are often vaguely worded, so you don't know exactly what is expected of you and you don't know what your results are supposed to look like. This led to the homeworks taking (me) upwards of 8 hours to complete. However, Meyer and the TAs are VERY helpful in clarifying what the questions are asking for and what you should be looking for in the final result. For the love of god, I cannot stress this enough: go to office hours every single week. Every 10 minutes spent in office hours saves you an hour of frustration. If you have any exposure to coding, then python is a very simple language to learn and not the main obstacle when it comes to doing the homework.

The grading scheme was:
Final Project (30%)
Midterm (30%)
Homework Assignments (20%)
Class Participation (20%)

Our year's midterm was hard (supposedly the hardest in the history of the class according to the TA), but it is about half easy-memorization questions and half hard-application-of-statistics-equations questions.

The final project is a group project where your group has to come up with a novel data analysis of some biology related data set (although it doesn't have to be biology related, a couple groups did analyses on video games such as pokemon and super smash bros). The difficulty of this depends a lot on what kind of model you decide to implement and the data that you are using. If the dataset is poorly formatted, then a lot of your time might get sucked into reformatting it. If your model is finicky, then you might not get any conclusive results (which is perfectly fine).

Class participation is mainly just general class participation and getting feedback on project proposals before submitting, so this should be a free 20%.

Terrible class, and meyer was unfortunately very unclear and unhelpful. Seems like a nice enough guy, but just had no good structure or idea how to teach concepts effectively. The concepts were disjoint, random, and not useful to anything we have done or need to do later. Also why is it in python if we only have to learn C++, but we never learn how to do any of the code, he just gives us complex problems.

Very, very disorganized class, where the workload is ostensibly reasonable...until you get stuck in the lab an extra hour because there were no supplies and so each project group had to wait their turn to use the singular available pipette / trypsin / vacuum. My entire lab group was delayed over an hour twice because of circumstances where some important experiment component was either not present or not available in sufficient quantities, which is not fun when it's already a 3 hour session to begin with. Guidelines on project reports were relatively vague and sometimes inconsistent depending on who you asked (Professor Meyer and the TAs did not seem to have the best communication).