The course with the IBM Lab is a very good way to learn and practice. The tools we've learned in this module can supply a good material to enrich all data work that need to be presented in a nice way.
Great course, one of the best course to get hands-on learning for Data Visualization with Python. Particularly the lap exercise, it will make you think on every line of code you write. Excellent!!!
par Mark S•
Very poor. As the course carries IBM's name, I expected a premium product, but I was disappointed. The training videos were brief and didn't go into the material in any great detail, and certainly didn't prepare the student for the lab sessions or the final assignment. I learnt more from Stack Overflow than I did from from the training videos.
par Ana C T M•
Links did not work for classes hands-on exercises, repetitive video explanations, and final project required content that was not explained in classes. Overall, it was a bad experience on a subject that should have received more thought and caring from instructors on lesson plans and class materials given its importance.
par Sean H•
Labs and lessons did not adequately prepare me for the peer review lab. A lot of information went through quickly or was hard to reread on account of the sheer volume of charts created. Minor gripe but when learning pie charts the videos mention pie charts being awful without properly explaining why they are awful.
par Steve K•
Almost all videos included the same bit about getting and reframing the data. This was a significant portion of the videos as well.
There seemed to be more confusion around the final assignment judging by the amount of questions in the forum. The assignment needs to be rewritten or made more clear.
par Juan C C•
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 Worst of all, the tech is outdated.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.
par Mo S H•
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.
par Abeer S•
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.
par Gabriel A•
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.
par Aniruddha P P•
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! :)
par Elvijs M•
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.
par Gisella B•
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.
par Pokkunuri S C•
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.
par Sema K•
It was by far the worst course I have taken in this specialization... You really should renwe the materials and add more labs, because video lectures are kinda useless. I am giving 2 stars out of respect for the effort given to put it here.
par Adam H•
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.
par Connor F•
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.
par Prajwal A T•
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.
par Panos P•
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?
par 清基 英•
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.
par Stephen v•
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.
par Tara S•
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.
par Federico T•
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
par Ermek A•
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.
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.
par Andrew S•
Not everything that was needed in the final project was covered well enough (or at all) in the videos and lectures
par VIJAY V S•
Very theoretical, Quiz questions were made over complicated. this make loose interest in completing the course