Labs do not help solve assignments. They must explain examples to learn, I have to research in google to solve. those practices are bad I don't like this way of working at all

I have to resubmit final assignment many times and wait for peer review for so long only to be reviews unfairly. Course needs grade moderation for peer reviewed assignments.

Material was good, videos were not. Poorly produced with noticeable track/volume changes within videos. Instructor was very bland and continually repeated himself.

I felt helpless while doing the labs. The videos are not descriptive enough; especially, the content for week 4 was not sufficient to do anything in the labs.

The final task is too complicated for what we've learnt and when looking for help in the forum I've received no help, so I have been stuck in there for days.

This course does not do a good job explaining visualizations and how to plot graphs. More time needs to be taken show how to set parameters in the exercises

Teach fundamental skills. not something like how make your font size big or include colors. Make assignments a fundamental activity not a complex activity.

only course i actually didnt like. incomplete and it was easir if obly send us to cognitive labs directly, the difference is that cognitive labs are free.

The tools for practice the code in python don´t work. All the tools in cognitiveclass.ai have some error message and I can not finalize my studies.

This was the worst course in the specialization.. It was hard to follow, there weren't many lessons, and it wasn't worth the cost.

One should take another course on coursera to pass the final assessment since the tasks are not covered in the course.

T​he IBM notebooks arent working in any of the courses included in this specialisation course. Its a waste of money .

Absolutely bad instructor with the videos not elaborating enough and the labs not functioning properly. Please fix it

So far this is the worse course- the coding is not well explained and the lessons are extremely ripetitive!

The videos were very repetitive, and didn't teach you much about best uses for diferent kinds of graphs.

Bad instruction to finish the assignment and not enough tools to get the objective done

Just Awful. Test is nothing like the practice modules. Very poorly done.

Total emarrassment for IBM

This course provides lectures that enable learners to understand the theory, application and practices that data scientists use to create meaningful visual presentations of complex data relationships. The labs provide adequate opportunities to do hands-on end-to-end work with data and visualization tools. The learner is challenged to go beyond the scope of information presented in the course to also search other resources to gain the knowledge necessary to complete the final project. Searching for additional resources builds a foundation for independent future work.

The final project was somewhat more challenging due to some file downloading issues. But I was able to get some help in the forums for that, which helped me accomplish my goals.

I learned and understood how to make graphics based on a previously clean and standardized data source. I liked this section.

Really good course with easy to understand materials and wide varity of visualization techniques and tools.

The assessment was really complex, but the course overall is really usefull!!

Amazing course!!!! I liked your very detailed and well-organized notebooks <3

The course was overall, pretty good. Although it was extremely repetitive with regard to 'cleaning' the data, the information covered was explained and shown pretty well. The lab sessions were detailed. I would have liked to see more of the possible implementations as opposed to manipulation of the aesthetic. I also hoped they would cover seaborn in more detail.

Although most people are against the final assignment, I actually enjoyed it as the previous courses gave us a jupyter notebook with most of the work already done, only letting us write the main part of the code. Coding from scratch with just the dataset helped me understand the topic better and will definitely make it easier the next time I attempt data visualization.