Nicely paced. Breaks material down into nice bite-size pieces. Labs helpful and mostly good instructions, had a few "what's wanted here" moments, but most issues were brain farts on my part.

nicely explained. grasped all the concepts quickly. Would give 4.5 stars if possible. 1 star less, because the programming assignments could be a little bit less guided and straight forward.

Good course. I'd be more happy if the reading sections are more helpful and contain more references. Not just summary of the video lectures. Overall, good introduction to NLP for beginner.

A decent intro to get into NLP I guess. From practical standpoint, feel a bit like this is bunch of semi-heuristic methods that are bit dated. Could use some more big-picture motivation.

The material was a little shallow in places, and there are some long standing issues with assignments and quizzes that remain unresolved. Other than that, it was an interesting course.

This is a quick and effective way to learn the basics of NLP. The course requires some understanding of linear algebra and calculus. The difficulty of the exercises is just right.

EXCELENT MATERIAL AND VERY CLEAR!! All the lessons and videos explained in a great way the exercises and theory. Just the final assigment was tricky and sometimes confussing.

This is a very good introductory course, unfortunately, it lacks depth. The rest of the things are amazing, as expected of deeplearning.ai, it was an enjoyable experience :)

I think this course is a good complement to other AI/ML courses from DeepLearning.AI, but previous courses are definitely recommended to get the most benefit out of this.

Good content, well-produced videos. Assignments are a little weird at times, but overall a good balance of showing what you've learned and not having to do all the work.

Well-build course, but as for me is quite superficial, I love deeper approach in teaching how things work and why. Although practical skills have definitely increased!

This is a beginner level, simple course for someone who is very new to ML/NLP; not challenging. Assignments are okay - the last one is the most useful/interesting IMO.

It feels me great to learn , via online media in this time of pandmic and yes of course the content quality is good , and so will continue to go for all the sessions.

Though i felt last assignment was pretty tough adn i had to seek lot of online material but overall vert nice course and gives introduction to nlp in very nice way!

Great content. It would be nicer if the lecture videos spend more time going into the concepts. Lab and Assignment notebooks however, cover the concepts in detail.

Content is well compiled. A lot of theory and practice There should be a programming foundation. And linear algebra It will help you understand the lessons faster.

I was sitting most of the time trying to reconnect to notebook. I don't know if this is the course fault or coursera's, but it exists. The content itself is good

Great course! What I'd really like to see more is how the embedding database is build (it was mentioned how it might be done but there was no exact explanation)

Videos were very basic (and short), but the workshops and assignments were thorough yet well commented (in code) allowing for quick progress and learning.

I loved it overall! here are some considers...some more video explanations and references would have made this more interactive and game changer

Its an awesome course, but it would be nicer if students can learn to code on practical projects instead of writing everything just from scratch

Nice content and easy explanation. There are a few mistakes in the programming assignments which should be corrected. Overall liked the course!

Exceptionally well conduceted course, but I got to say that the last two weeks are weaker than the first two in terms of depth of explanation.

The way the course is evaluated could be different, because it is too literal and sometimes you get to the same answer doing different things.

I thought the HW was a bit too easy. I understand this is MOOC, but perhaps some optional assignments that don't have as much templated code.