This is a crucial course however does very little in the way of teaching. The final assessment is also rather buggy. I could not get the dashboard to display in the provided online notebook, so I had to complete the tasks locally. You could argue that this serves better as a teaching aid, however the videos and lessons do not cover enough.

Although the idea of this course is good, it didn't have the same flow as the other IBM courses in the IBM Data Science Professional Certificate. There were no quizes during the videos, and the final project had concepts and code that weren't in any labs or videos. Even the hints from the professors in the discussion were misleading.

The first part of the course was good as I learned about creating visualizations for EDA. Unfortunately, the section on dashboards was not done well, in my opinion, and the final assignment was quite frustrating. I kept getting errors with my code but did not have enough knowledge from the course to understand how to fix them.

I learned from this course, however, of the nine courses in the professional certificate, I would say this is the worst. There are errors in the instructions of the labs, including being incomplete. Jupyterlab doesn't work (though they do say that it is optional.) I believe they need to reevaluate the content of this course,

I felt that the course was a bit disorganized. The actual code bits that were used in labs were hard to follow and material covered in final assignment required a LOT of independent googling of pandas libraries. Overall, it was a good overview but this course fell short compared to the other courses in this specialization.

This course was good but for too many of the final assignment questions I really had a to look up how to do it on the web.

A better explanation of the key_on parameter in choropleths would help - even though the entry in the json file is features - the key_on value is feature.properties.<key> not features.properties.<key>.

Needs further improvement, examples: (1) discuss important features/syntax ... go over it, may need not be too detailed but simple instructions on what the parameters do, (2) dont repeat throughout the case because it is assumed that the students knew it from the start so that other topics can be discussed or included.

Course was very hit and miss, fine through to the final section on dash boarding which was all over the place. Complicating matters was the fact that the lab sessions wouldn't run on the suggested site, meaning that they needed to be downloaded and executed separately on something like VSCode or Google Colaboratory.

The course is nice, but there are several issues that could be easily solved:

Some of the notebooks on JupyterLab were not working (e.g. "exploratory...").

On the final assignment page there were some bugs regarding the upload (i.e. question 3)

The videos in week 5 were too condensed and resulted hard to follow.

This course is a little disappointing for me. It is a 3 Week course and content you learn in this course are not even cover introductory sections. The Final Project is So hard, that it didn't cover the important sections. I don't suggest this course if you are really serious about Data Visualization.

None of the labs data imports worked. The majority of the video content said to take the time to really learn the topics via the labs. The final assignment data sources worked, so at least that could be completed. Paid courses really need to have external dependencies reliably available or updated.

The content was really interesting and I learned a lot. I just wish the code was explained better because there were a lot of times where there were functions I had not seen before and were not explained. The final project was also a humongous pain to complete do to graphs not being displayed right.

Good content to know. Fair but not great in terms of presentation. Many videos repeated how to prep the data frame so you end up watching the same 2 minutes several times. Also a lot of the things you had to know you had to figure out on your own versus finding it in the material presented.

Still good overall but not as well designed as previous courses in the IBM data science certificate track. The final assignment is MUCH more difficult than any content in the labs and harder than previous final assignments, which isn't necessarily bad but it's inconsistent and unexpected.

Covers a lot of ground. Dashboarding section could probably be a class by itself. Part 1 of final project was grueling, needs a better dataset and rethinking about what the visualizations are supposed to portray. Part 2 (the dashboarding part) was challenging but ultimately rewarding.

I didn't completely understood the labs and where some lines of code came from. Also, I felt that we don't get enough directions to complete the final assignment, not even which notebook to use. This has been by far the most difficult course of this training in my opinion.

Great course except of the final assignment being based on a deprecated or soon to be deprecated version of Folium Choropleth implementation. Please review that part as it could be very confusing to students that do not use cognitive class as their development environment.

The curriculum is fine. The questions and assignments are not. Way too many errors and contradictions. Final assignment questions were extremely unclear, indluding asking that we proved that interactivity was functioning by submitting screenshots, etc. Really needs work.

The material of this course is precious, however, the explanation given in Week 5 regarding Dash are too superficial. They should have added a video explaining carefully how the Dash interface works, since it may be really confusing for us who only used Jupyter Notebook.

Since students weren't able to submit code, this made it extremely difficult to answer the final project (which I couldn't figure out how to finish). Getting feed back on how to correctly code the answers is more important than showing a screenshot of the final product.

Need more clarity and practice for this course. This course seems the toughest as it asks for memorizing artistic layer syntax which seems so difficult coupled with the humongous choropleth map!

A huge amount of practice is needed for this certificate even after labs!

Course is good overall and have many useful labs. But final peer-graded submission is written extremely ambiguous. When I graded the others, I found that everyone did different screenshots, so it means that it was not demanded clearly what screenshots are required

The pace is too fast and the content is unclear from the middle of Week 3 to the completion of the course. Many ambiguous directions. Many of the codes would have to be ignored since they would not be explained why they had been used and how to utilize them later.

The instruction is okay. It should have more details. The labs are good for practice, except the final which is not clear instruction. Also the instruction for submitting result is not clear and the page is poor designed (text lines and boxed are not aligned).

Good approach to basic concepts of Matplotlib and other tools to visualize data with Python, but the assignment and final evaluation require much more knowledge than those taught during the course and, eventually you spend more time googling concepts on websites.