"致郁“

This class is so much more of a headache than it is worth. Somehow I would go to lectures and be more confused about various topics than just going into a topic with zero info. Like a typical Wu class, grade breakdown was 7% quizzes based on completion, 45% Homeworks (6 total, one of which was during finals week), and 48% Final. We received zero feedback after the 2nd homework before taking the final. Basically, you have no idea what you do or don't know or where you stand in the class. The final exam was also quite difficult and half of it was nothing like the previous quiz or homework questions.
I watched all of Prof Chen's 102c lectures on youtube before the final (HIGHLY RECOMMEND) and finally understood the course. It's clear to me the difference in teaching between the two professors, so I would try to take this course under another professor (if possible).

2022 spring, I'm currently stats102B with Wu. Wu is not posted as a professor for stats102B, so I'll leave some comments here.

1. Wu's lectures usually composes of the following: 25 mins of review of last lecture, 5 mins of new stuff, and 20 mins of stuttering.

2. First week of lectures, if you thought that you are taking math 115, then you are in the right stats102b class. Wu starts out the first two weeks talking about linear algebra, but he doesn't tell you why.

3. You are expected to master linear algebra. He will do a simple review of it in the first week. You are responsible for knowing every math proof by heart.

4. Wu does not set up any official Q&A forum such as Campuswire or Piazza. So, do not expect any online hw help from professor. He won't reply you in time

5. Wu's lectures don't have the big picture. If you wonder what a big picture is, go checkout Miles Youtube lecture on stats102B. It's public, and first or second class he tells you what the big picture of machine learning/optimization/modeling is.

6. Wu's lecture notes gives no example R code, but all homework is in R.

Take 102a with another professor if you do have choices.

Terrible. Just terrible. Gives a lot of arbitrary extraneous specifications for the homework that are either easy to miss or incredibly unclear such that if you fail to meet those specifications (and it's all to easy to do so), you'll get heavily penalized. In addition, grading for the homework was screwed up and a regrade had to be done, but even the regrade was screwed up. Incredibly unresponsive to emails. Goes through the most difficult topic of the syllabus two days before the exam, and sets up over half the questions in the exam to test that topic. I have never ever hated a module more in my whole academic life. I legitimately got anxiety from this mod. Do yourself a favour and skip this module/prof if you value your sanity and mental health.

DISASTER. DOESN'T know how to teach. DOESN'T know how to make clear slides. DOESN'T know how to grade (highest score for the final project is 84%). The ONLY thing he knows is how to make easy concepts more confusing. One of the worst stats profs I've ever met at UCLA for the past six years.

Bro just fired him

I had the misfortune of taking this class with Professor Wu. His lectures are incoherent and don't make much sense at all. Reading the textbook is much more valuable than the lectures. He is mildly helpful during OH, though he was 20-30 minutes late multiple times. He is a nice guy overall and I believe he wants the best for his students, but his teaching style is better suited for graduate courses.

Professor Wu is very nice, but his lectures are extremely unengaging and unclear. He recaps the previous lecture for at least 10-15 minutes every class, and then when he teaches new content, he half reads off the slides and half does some math without really explaining the big picture of when/how to use the methods being introduced.

The class is pretty challenging compared to the complexity of the content just because they are not presented very well. We did not receive ANY feedback for homework after homework 2, and none of the solutions were posted because "the exam is based heavily on the homework." Is that not the whole point of studying the homework? There is zero transparency in this class and Professor Wu's teaching model is to just lecture and assign work. There is no consideration for students' progress and whether or not the previous lessons were actually effective. The way he teaches was more suitable to an online course, since his lectures are so unclear I would've had to rewatch them multiple times just to understand the objective of the lecture.

I would have liked to look to the slides for help with homework, but the slides are equally unhelpful since they only contain the most basic algorithms and examples, but rarely information about how to apply them in different contexts. I also found the notation pretty confusing and I personally had to spend a lot of extra time watching Professor Chen's STATS 102C lectures (posted on Youtube) to understand the lecture and the intuition behind many of the sampling and integration methods. While I didn't mind the theoretical nature of the class (I found the proof based homework problems to be the easiest), I found it very difficult to understand any of the math when there was little explanation for its connection to what we were learning.

Since homework tended to be more complicated than lectures, I felt like I had to self-learn a lot using the textbook. In general, I don't recommend taking this class with Professor Wu if you have the choice, but if you find yourself with no other option, prepare yourself to dedicate a decent amount of time to just understanding the material and rereading the textbook.

Taking 102A and 102B with Wu was the worst decision I made in my three years at UCLA.