Honestly speaking the video materials are not at all sufficient to understand the concepts. I have to watch other YouTube videos to understand concepts.

I've got strange feelings about this course. If we are talking about courses from deeplearning.ai, it all started with Tensorflow in Practice specialization.

This course have should have 2 weeks or maybe one, because everything can be accomplished in a few days.

It has very small amount of interesting content.

It is repetitive (some parts of assignments are copied from Deep Learning specialization assignments).

The video lessons are strange - it seems that two instructors recorded same videos and only beginning and ending from Łukasz Kaiser's videos got to the course (which is not fair).

Some procedures don't have description for function's arguments. Some procedures don't have testing function - you don't know if it works or not.

This course should be a part of another course, because it doesn't seem as a complete course. It feels like it doesn't completed, like it is a draft for a full course.

I believe that others courses from this specialization will be better. If you know Russian, I suggest you to take course about NLP on Stepik platform https://stepik.org/course/54098/syllabus. It is much better.

I came in with high expectations based on prior experience taking Andrews Ng's Marchine Learning course and Deep Learning specialization. Unfortunately, this course did not come close to meeting my expectations. The quality of the lectures is generally rather poor. The only real purpose they serve is to introduce terminology so that the student can seek better lecture material elsewhere. Some of the assignments may be interesting to folks with no prior NLP experience, but most are pretty basic to call this an intermediate level course. I recommend that folks fast-forward through the course lectures and find much better material available on youtube. Overall, I am pretty disappointed...

Good explanations, covers some fundamental concepts in text classification and vector embeddings. Not a wholesome introduction to NLP and Text Analytics if that is what you are after

The instructors left out too much on the intuition part.

I can not give a good rating for this specialization. The teaching style seems antiquated to me. Instructors are reading text like an AI from a text ticker (you can even see the eyes moving). Sometimes the quality is not good ("plopp-noise" because a bad microphone or headset was used). The Jupyter Notebooks for the Assignements do hang often. Moreover I think the quality of the code could be better. I'm working through the Specialization because my employer paid it. I can not say, it's very motivating. Despite my negative review, I learned something from it.

It was the worst experience I have ever had. It is just pain with no gain. The instructor was too young. The lectures were not explaining anything that was included in the labs. The course learning objectives were entirely different from the course itself. The course requires expertise in python that is not written anywhere. The lectures and Labs are in different dimensions. Everything that you want to learn will be in assignments that will not be taught in course lectures. It means that all the burden will be on your shoulders. Lecture videos are just about the intro and expect everything as an expert to be done in the assignments. It seems that it's a blog instead of a taught course. It's better that we go and read the blog related to NLP. Labs are all useless. Some labs are having errors that waste too much time for students. Poor support.

I am not satisfied with this course as it contains very long assignments and even after completing the assignments, i am unable to get any grades because of errors. Have reported errors too but no any quick response.

Poor quality of video content

Persistent issues in accessing the labs (It hangs 50% of time)

Well paced and easy to follow.

There are some typos here and there (so the course might need some more polish on that end) but, apart from that, it's accessible and puts the focus on understanding the concepts rather on coding contrary to what I have read in another review.

You could follow the course even with no prior experience in Python.

If you take the course, don't skip the ungraded assignements, they are an integral part of it and provide more detailed explanations of what has been taught in the lecture videos.

Thanks to the team and good luck all.

I really enjoy and this course is exactly what I expect. It covers both practical and conceptual aspects greatly and I recommend everyone to enroll in this course to make their NLP foundations strong

A really great course in NLP. They do a really good job balancing beginner and intermediate skill levels. This is a good introduction to NLP and machine learning in general. Really fun course!

Fun, interesting and useful course. A couple of road bumps in the assignments made me waste a lot of time, but the forums and Slack channels were lifesavers in those situations.

I has the right mix of challenge and support. I gained new insights into topics that I thought I already understood well. Great introductory course.

Very helping in understanding the maths behind NLP for classification methods and I can see these things more intuitively from now on

Good job! The course material is easy to follow and the links to related material is appreciated.

Great course, very good materials and explanations! ❤

A high quality course overall! It helped me understand both theory and the programming mechanics of implementation. The Jupyter notebook guidance was detailed and well-organized!

Enhancement opportunities:

I felt the PCA lectures and PCA function implementation were a bit muddled. Consider illustrating the geometric intuition behind PCA: when 2-D data points are projected onto a line, the "best" line maximizes variance along the line while minimizing the reconstruction error of the data points.

The final notebook assignment is long and contains a large number of function and global variables. It is a lot to digest. Maybe enhance it with a takeaway video that unlocks after the assignment is passed. The video will visually recap what was accomplished by showing the start-to-end pipeline.

The course is a great value for the price!

Good overall, but there is room for improvement. The video lectures can be improved upon -- many of these are essentially the lecturer reading over a high-level description of a given concept, as opposed to detailed explanations (e.g., SVD & PCA topic). The unit tests for the assignments also need to be more robust and/or error messages generated by the auto-grader need to be more specific. You should not routinely see cases where "All Tests Pass" for ALL cells in the assignment notebook and yet the auto-grader fails to assign credit for 1+ modules, forcing the student to trouble-shoot issues that were not caught by the unit tests and for which the auto-grader error logs are unavailable.

I learnt a lot on this course - the material about matrices and matrix operations was all totally new to me, so it took a while to get my head around (more background reading links here would've been helpful). Also, with some of the grading cells in the assignments it was difficult to understand why the answer was being marked as incorrect (examples being UNQ_C11, UNQ_C22 in the week 4 assignment).

You must have a very strong knowledge of python to do this course. Concepts are explained well, but work submitted often goes beyond explanation. I found I understood the concepts but had difficulties with the intricacies of pyhon, numpy and various syntax.

The first three weeks were taught really well. But I found the explanations of LSH and Hashtables rushed and they could have given more time to explain it. The assignment in the 4th week was very tough

Ok but coding exercises could have been better structured (e.g. less long functions without easy to run test cases). The exercises could also have been a little more stimulating.

Some of the instructions were very unclear. In the last section, they started linking to explanations of some terms, which would have been really helpful earlier.

Great course, with interesting examples. However, I am dissapointed with the automated grading system, which wrongly penalized answers and impacted final grade.