Content was solid, but videos mostly said "go do the labs" vs offer meaningful tips for the final an beyond. Worst of all, the tech is outdated. I spent an entire weekend working on the final assignment due to technology issues. An embarrassment for Coursera and IBM that they let this happen.

Better to read matplotlib and folium documentation and look for answers from stackoverflow.

This course didn't offer enough components of matplotlib and folium.

This offers lab sessions but they are not main contents.

Final assignments are impossible for someone who just takes only this course.

The teaching pedagogy wasn't as good as the other courses I have completed in this certificate (Professional Certificate in Data Science) so far.

Questions in the assignment were related to topics that were not discussed in the course. I had to search online and complete the assignment.

This course is in need of a healthy overhaul from content to lab to final assignment. I would recommend adding a recap "week" just for data frame manipulation. As with many of the courses, the labs could use some proofreading and updating, this course skips around a lot.

The course can be made much more better. The final course assignment wasn't much based on the things that were taught during the course. Example could be using the labels above the bar.

On the bright side, the contents were really good. Thanks to the instructors! :)

As all the other courses in the specialization, the depth is rather shallow. The seaborn and folium parts are extremely short and superficial. Good luck if you actually want to apply these libraries for your own projects -- then you're back to googling.

The final project was a huge waste of time. You have to program in the Dash tool which most will never use and it only works on the IBM cloud which most will never use. The Jupyter dash programs didn't work which was a common complaint in the forums.

Hay una sección que repiten en casi todos los videos. Además no funcionan los laboratorios desde hace días , no puedo hacer el trabajo final porque tampoco sirve el link y no hay manera de comunicarse con los de servicio al cliente de coursera.

The videos had low sound quality, almost all videos had same recording for initial 2 minutes which was unnecessary. The final project had use of many such functions which were neither discussed in the videos nor explained in the Ungraded Tools.

Had some problems with changes to the interface that caused quiz questions to become unreadable. Also found some of the discussion around artist and scripting layer in matplolib difficult to follow. Could have done with more explanation.

The marking rubric on the final assignment gave 5 points or no points for a table, so there was no way to give part marks. Also the previous labs did not show how to add the SF map in the same way as the final assignment.

As compared to other courses in specialization, this course has many errors in labs. Video sessions are also less informative. All the things directly come to lab only. Also error resolution by faculty is very poor.

The level of dificulty of the final assignment does not correspond with the contents. It was so difficult and there were a lot of issues related to the platform. I spent more than two months in this course.

The final project was way difficult. Which is fine, difficult is fine, as long as the knowledge on how to solve it is provided by you in the lecture notes\videos\lab sessions. I mean that is your job right?

I was so upset for the last project because knowledge of I have learned from this course was not enough as all for completing all the questions. I really wish to get more advice or tips for the project.

Doing the IBM Data Science Certificate and this is probably the worse course. The content is relevant but the directions and labs are poor compared to the others. The explanations aren't as clearn.

A lot of problems opening the labs. The final assignment required us to do things that were not discussed in the course and it was unclear where to get the relevant information to complete it.

Video lessons are poor in explanation of matplotlib syntax as well labs. Differences between pyplot and artist layer are not clear: a lot of work has left to selftaught. Kind regards, FT

Some exercises throughout the course aren't explained neither in the video, nor in the labs.

It is hard to understand the Authors data visualization functions explanations in the course.

The Dashboard week is a mess, nothing is explained enough and the final assignment is awful broken code wreck that maybe works for only about half the people.

This Course wasn't that good like the previous ones, the Videos were quite short and the labs weren't very explicit and made to be understood by everyone.

Not everything that was needed in the final project was covered well enough (or at all) in the videos and lectures

Very theoretical, Quiz questions were made over complicated. this make loose interest in completing the course

Very frustrating experience with lab. Not all labs works properly at least on my home computer.

I am happy with what I learned but I think it is not as good as the rest in the series.