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.

I liked this class as an introduction to NLP, but I don't think it went too deep into any topics. The first homework was presenting on a NLP paper and peer reviewing, which I thought was interesting. The second homework was a bit more bland, but I think Professor Peng said she is going to change it after student feedback. Project is also very doable in terms of workload since there's only two homeworks. Exams were really fair and doable as well.

The professor really seems to care about learning and student feedback, so I can only imagine that this class will get better and better as more iterations are offered!

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.