I would avoid this for people not aware about mathematics behind (pca might be tough). However, good mix between skills gotten from de deep learning specialization. Just one thing upsetting, a 90 out of 100 due to an issue in the downloading of nltk which led to not pass tests.

It was a fairly good course, but I still expected a bit more from it. The coding assignments could have been improved. rather than making the assignment "fill in the blanks" type, make it more research project oriented. Overall a good exp, learned a few new skills. Thanks!

The course is very good in building intuition of important NLP topics (lectures especially). I would love the labs to include non-numpy tools, otherwise much of the effort goes into figuring numpy out, rather than trying to use the intuition from the lectures in practice.

The overall subjects are OK. I think this specialization could be 3 courses instead of 4. Some videos are too short and needs some more explanations, especially the LSH was unclear for me. The last assignment was harder than usual for me, especially the last part.

Props / videos which show real visualization can improve by a lot. Exercises though easy to medium, can be frustrating sometimes. The comments given for guidance are confusing sometimes. Support needs to improve rather than asking us to put on the bulletin board.

Quite good - no idea why the one trainer tells us in the videos he is going to teach us something and then the other trainer does all the work. And at the end he comes back to tell us what he taught us - but he did not. All he does is intros and outros of videos.

Although the course is great, the video lectures could go into more detail regarding how exactly to implement the theoretical concepts taught in python. The lack of this implementation explanation makes the weekly programming assignments unnecessarily difficult.

Good overview, it is quite basic especially if you have previous background on NLP but helps to you have an introductory background of the most basic techniques when treating word embeddings. Eager to keep the specialization to see how complex it would get!

There could have been more depth added to this course, this would make it more interesting. I liked this course, but on some topics, it seemed more of like we just touched upon and finished. So, adding more insights may be more useful to this course.

Course is really good - it covers variety of topics and has great notebooks prepared to write some code yourself with little effort. The only minus is that some topics seem to be detached from reality. One has to guess what they are for

Very well thought out course, great connections between the weeks and everything builds up into real world applications. I am fairly certain there a small number of errors in some math and some of the hero videos would not load for me.

Great concept and great teaching. I know this gets harder to evaluate afterwards but the labs seem too guided. In the end, we are wondering if the concepts are coming from us or from the laboratory formatting.

Great to begin with NLP

I was enjoying this course. But last week was not good. In the last week's assignment you have given everything, and have no clue of understanding why when how. I am disappointed because of last week. It was complete waste of time.

Great course on the theory part but the assignments should be more flexible when writing the code, it is just fill in the blanks which restricts you and because of the explicit instructions it is hard to dive in and concentrate.

A really good course that helps you get started in learning Natural Language Processing. It would be very helpful if you're familiar with some basic mathematical concepts of Machine Learning like Sigmoid function, PCA, etc.

Lecture is clear and concise. It's good to learn the high-level concepts of basic building blocks and foundation of NLP. However, the online programming exercise has some glitches that needs to be taken care of.

Overall the course was good how ever more intuitions could have been provided on the algorithm part. For example LSH, its short coming while performing sentence similarity tasks should have been discussed.

The course gives a good introduction into the basic concepts behind NLP. However, I would have liked to see some more exercises that really challenge you to implement longer sections of code on your own.

The course is great for gaining intuition about some topics in NLP (Preprocessing, Word embeddings). However, some topics are quite advanced and it will take a while to understand those (PCA, LSH).

Started off great, but I feel like the more advanced stuff could've been better explained. Regarding the exercises, I felt like the labs often gave too much information that made them all to easy.

The course material is very good but the code provided is not of the highest standard and the auto-grader is very idiosyncratic. There are typos in the comments in the code that are unfortunate.

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.