As an MSOL student, the professor seems to be good at communicating and is organized for the online section of the class. The assignments were doable, we were definitely given enough time to complete everything. The quizzes seemed hard. Practice quizzes were provided but the real quizzes seemed more conceptual with information that did not seem to be taught in class. The final project is also doable but there isn't much involvement coming from the professors or TAs to see how it's going. There's a lot of extra credit opportunities. Professor seems very nice and knowledgable on the topics in every lecture.

This course is for students who want to focus on research in the future. You should not take it if you are not interested in research. The professor's lectures are clear and full of knowledge. I have only a little knowledge about NLP but can learn a lot from her lectures. However, the quizzes are harder than I expected, although the average score is high. The practice quizzes only cover a small part of the topics that will be covered in the actual quizzes.

The workload is higher than I expected as well, not because the assignments are hard, but because they are time-consuming. The first assignment is to present a paper. Not only do you need to present, but you also need to write a reading note. (I haven't written a required reading note since I was in junior high.) The second assignment mainly focuses on human annotation. We need to compare the results generated by GPT with those annotated by humans. I think both assignments are designed for students to understand the entire research process clearly. They are not helpful at all for students who are going to find jobs unrelated to research.

The prof seems to care about her class, she responds very quickly on piazza, which I give her credits for. Unfortunately that's all the good things I can say about class. It actually pisses me more when the prof said in class the assignment won't be actually used in her research? Then why I am wasting my valuable time label those dumb datasets lol. Assignment 1 is not smart either. We are computer science majors, we do not like write a 5 page report just describe some random ChatGPT behaviors.

Please replace these assignments(also the final project) to some actual CODING project, such as write a transformer from scratch, GPT from scratch, translator from scratch.

Also it is pretty disappointing that the most advanced thing this class cover is transformers and some NLP jargons. EVERYBODY KNOWS TRANSFORMERS THESE DAYS. Please considering add more valuable content in your course.

Probably the best grad level course I have taken in UCLA! NLP area is not the same as ML/DL course but you'd better have some knowledge of DL before this course. This course cover traditional NLP techniques to the most advanced LLMs. Most assignments and final projects are research oriented. The content is also helpful if you are looking for jobs in AI/LLMs area. (They usually ask about transformer and attention in interview)

As for the course content, I believe it is quite fair. It covers a wide range of topics and explains the historical development of NLP. The content also balances concepts and mathematical explanations well. I personally think the course content is suitable for students with various backgrounds;

As for the quiz, I think it is unfair. The practice quiz should help us to better prepare for the actual quiz. However, the practice quiz is quite different from the actual one, which turns out to be misleading us. Also, some questions on the quizzes concentrate on unnoticeable details. Given what we have learned during the lecture, I feel like I am doing zero-shot or one-shot during the quizzes.

As for the assignments, the 1st one is fine. But the workload for the 2nd one is too overwhelming. And since the 1st assignment is already research-orientated, making the 2nd one even more research-orientated is unnecessary. I believe a better way is to have an application-orientated assignment for the 2nd assignment.

Good class overall. This class covers lots of useful information related to current NLP research. However, the workload is heavy. 2 midterms + 1 final + 2 big assignments + 1 final project seems too much. I have to admit that this workload is not as bad as it seems since assignments and the final project are actually not hard. But if we can cancel the final or one of the midterms, it will be more manageable.

Great overview of current NLP papers. Some NLP experience is necessary, but grading is very generous and mostly based on participation/completion. Not sure what the other reviews are saying since Prof Peng is really knowledgable, helpful, and completely fluent in English

Violet is such a sweet professor, and she truly cares about student learning. Her lectures really go in depth about NLP concepts, which was a bit overwhelming as someone who has no NLP experience, but she really tries to explain things in a way that is clear and easy to understand. She has two quizzes, which aren't too difficult (even though I didn't do great on them). The tricky part is that she really emphasizes certain aspect of the course, so you really need to make sure you have a good understanding of everything covered. The two assignments aren't too difficult, and I like that they introduced us to what NLP research looks like. Overall, she did a really great job, especially for her first time teaching the course.

162 with Peng was one of my favorite classes I have ever taken at UCLA. She is an amazing professor, super engaging, and cares for her students. Her tests are fair, and the content isn't as math heavy as other ML classes. Would highly recommend

Really great class for anyone with a little bit of NLP experience who wants to know more. Between homework, projects, and quizzes, there's good coverage of NLP basics, underlying math, and important existing research. Assignments are creative and go beyond just problem sets. Prof Peng and the TAs are super helpful and responsive. Lectures are engaging with a good amount of participation/dialogue with students. There are lots of extra credit opportunities.