I think the name of this class should be "Introduction to NLP research". For someone who have background in the NLP/AI research, the content covered is pretty basic. Assignment 1, which is paper reading, is pretty natural to a person accustomed to research. Assignment 2, which I agree is a bit of a chore, probably could be streamlined with API calls to ChatGPT API. Maybe that's what research in NLP is like? I don't know. I feel like the comments about technical details are not doing justice to the professor. I think this class is detailed enough as a research oriented class. (Even for undergrad classes like 146 or 145, the professors are not covering code implementation in class. Implementation is practiced in the projects.) Since the assignments are designed to be research focused, student don't really have the chance to practice implementation of algorithms.
On the other hand, as a research oriented class, I feel that there is too few material that comes from current ongoing research. The current form of this class is somewhere in the middle of the two worlds(content oriented/research oriented), which misses the merit of both worlds.
Therefore, I think the professor need to readjust the focus of the class. Advertise the class as a research oriented class. Put more focus on current research. Leave the fundamental content/implementation project to 162. Make 162 a pre-requisite.

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.

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.

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.