In each video we transform dataset and it take more 1 minute for each video. Will be good if in video will be some quick quiz as in "Data Analysis with Python" and "Python for Data Science and AI"

The Course Was Good. It would have been better if some lab sections were covered in labs. As we all know understanding a code then reading might help the students grasp better faster and deeper.

More in class projects similar to final assignment where we can challenge our knowledge as we are all remote and it takes time to communicate through the available coursera forums.

Thank you.

The labs were good but the issue was the extremely rushed up videos. A lot of concepts, especially the artist layer was not covered will in the videos, which made me give this course 4 stars.

I learned solid bases on different data visualization tools, it was an overall good course. The one thing I think could be better is to provide more exercises to work with the Artist Layer.

Good coverage of different plots. Videos are somewhat repetitive regarding the dataset (most of them could be about 20% shorter due to this). Labs (in Jupyter Notebooks) are great practice.

The course was beautifully structured. I would like to request to add the conditions on which tiles Mapbox Bright works. At times the tiles dont work and we are not sure of the root cause.

Kindly update the final assessment of this course work since it is quite difficult to work with it, as the content related to the assessment cannot be found in the course videos. Thanks !

I learnt an awful lot so I would give the course at least 4 stars. The opinions I got from the forums and the marking was that a lot of people really struggled and quite a few gave up.

Excellent course. The labs really challenge you because some of the material is not directly taught or the syntax differs slightly from what is taught so you have to hunt for answers.

Great Course, would have liked to have labs/exercises that coincide with the video as he is presenting. Instead, it is designed to watch the video then go back and complete the labs.

The course had a great examples and samples for common and uncommon visualizations. The course lacked the background to be able to import the geojson properly for the final though.

Good course, but I found the final assignment hard to complete, spent quiet sometime researching to be able to complete it. Providing the correct solutions would be helpful

Thanks

overall Good content. Guideline and explanations in Projects / assignments can be improved. Many times, instructions were not clear enough for a smooth learning and navigation.

Overall really good. However, would be better if a few videos added about object-oriented visualization. Also some links and methods used should be updated to the latest ones.

Best of the 5 IBM Data Science Courses I've taken so far. Some problems connecting with the labs, but you can bypass these by downloading the ipynb's from cognitiveclass.ai.

It was very nice and brief course but it could have been better. Some other topics must be included and some more exploration of different properties needed to be addressed

This course, although useful was difficult to follow at times. It did not get that into the Artist Layer of Matplotlib but the final project requires the student to use it.

It's an informative course, it even tested a student's perseverance and creativity in solving/bypassing various bugs. The final assignment was definitely an eye opener.

final assignment is tough. Everything else was decent and intuitive. Good jupyter notebooks and labs for practice were provided. Do practice all ungraded lab sessions.

Would've enjoyed the course more, if it got into the nitty gritty of annotations, but a comprehensive and decently delivered course nonetheless. Kudos to the IBM team.

The learning was good - I had a really hard time with getting the IDE environment and labs/assignments to work well. Doing screenshots over and over is inefficient.

Just like the few previous Python courses by IBM - errors and typos have yet to be fixed. But other than that, it is a really good introduction into using Matplotlib.

This is a very fascinating and demanding course when one follows all the Skills Network Lab exercises. The advanced visualization tools are worth the trouble!

Examples contained less python codes as compared to asked in final assignment. More python codes for visualization are to be conveyed.

Queries are not solved.