Comentários e feedback de alunos de Data Visualization with Python da instituição IBM

The labs were very informative, but the videos didn't add much of anything to my knowledge. The final assignment was incredibly difficult, and the course was all but useless for completing it. Almost everything for the final assignment had to be looked up elsewhere. When a final assignment tests over material never covered in the course, what purpose does it serve? There are many other reviews that have the same complaint. Something needs to be done to rectify this problem.

That`s a good course. I realised the Instructor efforts and his great skill and capabillity wich Python visualization. The final assignment pointed to activities that couldn't be deployed in another (or resident) Jupyter notebook, just only in an IBM cloud notebook.I expensed too much time trying to discover it. Some instructions should be better explained during the course. This is an important subject to be dealing in just tree weeks. Thank you.

The part of using the artist layer is a little ambiguous. Now after I finished the course I don't feel that I know clearly the difference between using the artist layer or using the scripting layer. In both cases we use plot function of a dataframe.

I think dedicating a week or more to discuss the actual functions and the way of using the matplotlib library may be better than previewing more visualization options like waffle chart and word cloud.

Sorry to say but this course is actually worse than the others in have learned before.

I understand it may be hard to teach only the different tools for visualization such as folium, bar/pie chart. However, the speaker in this course speaks the same "WORDS", just like replacing the variable names when coding under instructions.

I did learn something in this course but just don't like the way we been given.

This course had several areas where it could be improved: (1) The Final Project was made much more difficult by requiring the students to use skills which were not taught in the course. This seems to defeat the purpose of testing, which is to test what was learned. (2) The course should have contained content which explains when it is more appropriate to use the specific types of visualizations.

Overall a good course, especially the final assignment is well done. However, there is too much focus on the class labs and practically no effort put into the videos. Within the class labs there are only comments as reference to how and why something is done which often lacks proper explanation (e.g. what the called methods in a chart mean, how loops are used to fit data etc.)

I have nothing to criticise except that all these tools could also be taught without being dependent on the IBM platform. It's not a bad platform, it's just that you heavily rely on the internet to complete assignments. That's a bit frustrating if you want to complete an assignment while you're on the road or just have a bad connection in general. Except for that: flawless!

I felt this class was not bad.... I do think that the quizzes are a bit too easy with the assignment being a serious step up. The assignment also required you to Google some how-to's, use some patches and reference prior courses which I feel asked a lot of learners. The info is good, the skill learned is pretty cool. Not the best class, with definite room for improvement.

The material we learned will be useful. But, the Week 5 assignment had to much busy work concerning making screenshots. I got some tips on the forum though that allowed me to make the submissions while minimizing the number of screenshots I took. Hint: create the app with mode equal to 'external' instead of 'inline' and print save the resulting browser tab as a PDF.

It was a good course. I really enjoyed it when the labs worked. The labs did not work most of the time. It was frustrating and degraded the learning experience. I spent hours combing the forum and the Internet to find solutions. I was desperately afraid that I would not be able to complete the final assignment. I am glad I was able to finish.

I thought the final assignment shall be focus on Matplotlib and seaborn, but found it was only about "dash". And it is too complicated and exhausting with many bugs. I don't think python has advantage to build a dashboard since it is much easier to use Tableau and Power BI to build it. The final assignment should be restructured and improved.

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.