STAT 5430

Breakdown of course grade: 30% HW, 30% labs, 30% final project, 10% participation.

Overall, this class was fine. Some negative reviews down below make the course out to be much worse than it really is in my opinion.

Taylor Brown is a very cool dude. Overall, he's chill and pretty funny. As a professor, since he does the flipped classroom situation, he doesn't really teach much in this course: he's there more for clarification purposes/ to help if you're stuck on a coding question. The way the class works is basically you show up to work on whatever lab/HW is due in the next few days. Labs are assigned basically every class and can usually be done in the 75 minutes you're in class for. HW are assigned less frequently (8 in total) and are just longer/ a bit more difficult version of the labs. Literally every assignment (lab, HW, project) is broken into an R coding and python coding section. As some of the reviews mentioned, you won't necessarily gain that much *new* skill especially if you already have experience in these languages. However, I found the frequent assignments really did make me more adept at coding in R and python and definitely allowed my code to be more efficient/ readable. Essentially, this course prepares you for the coding final exam you need to pass to stay in the stats masters program: the exam is very easy if you kept pace with the assignments (I think I studied for like 2 hours total and easily passed).

However, I can see this course being a struggle if you've never had experience with R or python, but tbh I feel like most graduate statistics students should have experience with these programming languages lol. Grading is pretty fair. Yes Gradescope is very annoying but idk any way around it. If there's issues with the autograder Taylor fixes them and gives points back so not really an issue. Overall I'll end up with an A- in the class with is honestly fair for the amount of effort I put in so I'm not even mad. If you try to attend class as much as possible, get some friends who know how to code relatively well, and stay on top of your assignments, you should easily get an A-/A depending on how much work you want to put in. My only compliant is sometimes the HW/labs take longer than you would expect but as he literally doens't even lecture in class, you should have more than enough time to complete them.

#tCFfall2021

This course is literally the weirdest and most confusing course I've ever taken. What this course is is a series of programming exercises. Professor Brown is a nice dude, and I feel like he would be very chill to hang out with. As a professor, however, I can legitimately say that he taught me nothing I didn't already know before. I had done alot of Python and R prior to this class, and when I saw the syllabus, I thought this was going to be a review of those concepts plus some extensions. What I got was a series of difficult programming tasks that 1.) did not make sense (he asked us to find the median of a bunch of nan variables) or 2.) had super unclear instructions. The grading is also ruthless. He uses an autograder, which is buggy. I don't know what grade I'm going to get, but if he goes by raw score, I am so dead. I stopped going to class two months before the semester ended, since the class was at 9:30am and it was a flipped classroom setting. The only thing I 'possibly' learned was functional and object oriented programming in a statistical setting, but this was just one unit out of like 8. I feel like if you went into this class knowing 0 Python or R, you would get absolutely destroyed.

I'm going to be real right now: if you can avoid this class, avoid it at all costs. I've taken horrible courses before, but this was by far the worse. I dreaded doing the homeworks and labs, and I am dreading what my final grade will be, and all I've had from this class is just frustration.

This course isn't the most difficult course per se, but that doesn't mean it was a good one.

Let me start with the assignments. The grading scale is 30% homework (about once a week), 30% labs (in-class work), 30% projects (2 of them, both due at the end of the semester), and 10% participation.
The homeworks and labs were kinda the same thing, only that the homework were larger, and were due much later than they were assigned, than the labs. They were both group work, and they were also equally frustrating. The professor used Gradescope, which is infamously known for being vague on what you were missing, when you were getting something wrong. He also didn't word questions well. Sometimes, he wasn't clear on what he was looking for in terms of a solution. Other times, he wanted something that was pretty much impossible with what he expected us to know (more on that later). Other times, it was a typo. Regardless, it was ridiculous to have to spend hours and hours deciphering his wording.
The "projects" are really high-stakes homework (group work as well). I don't have much to say about them yet, because I'm still doing them, but I hope I can understand his wording, because there's ZERO visible Gradescope tests.
Participation is literally going to class (difficult for a 9:30am) and filling out a poll.

Next, there's the professor. Professor Brown used the "flipped" classroom style, where we did labs in-class, and should've read the textbook beforehand. The textbook is worthless: it gives you the most basic concepts, and doesn't really explain much else. That being said, he didn't really teach anything, so it's pretty much a do-it-on-your-own kinda class. The good news is that he's pretty responsive to email and Slack (our form of course communication). I gave him a low rating because he's really bad at wording questions.

Expectations: They assume it's an introductory programming course. They assume incorrectly. This course could be difficult at times for me, someone who had taken STAT 3250 and 3080, and had to solve some assignments using things taught in those classes but not 5430, so please make sure you know Python and R beforehand. They also assume you've taken an intro stats class, but make no assumptions with regards to math. I feel like they upheld this, as when they explored math concepts, they made it such that we don't really need to know much about them.

Overall, I'd avoid this course, because the professor isn't great, but if you take it, get a good group, preferably with smart people who can actually understand what Professor Brown is saying. If you have a good group, this class will only be moderately difficult at times. Make sure you know Python and R beforehand (STAT 3080 and STAT 3250, or equivalent) as well.

#tCFfall2021