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Great course! A couple of comments:

I think this would benefit from more rigorous statistical analysis - possibly as a follow-up course. When I did this with data in August the relationships were very different since they were only taking a snapshot in time (i.e. the maximum point) of infections regardless of when this was, the population etc. In a follow-up, it would be useful to understand how to establish causation i.e. weight the datapoints by population or by testing / population

This is my first time doing a Coursera Guided Project. I love the interface as it allows us to watch the video and follow along in Jupyter Notebook at the same time. I've just completed a basic course in Python and this project was very helpful in reinforcing basic concepts. From a statistical POV though, it could be a bit sweeping and misleading to draw conclusions from the visualisations when the correlation between the variables are so low.

It was generally a good project to give a try even for beginners. I took this project to remind myself of some skills and was quite helpful. But still, there are some downsides for sure but not that cumbersome. One thing you have to know is that the lecturer isn't a native speaker...

This is an interesting project. But I think there's more that could be done. The infection rate and other variables have low correlation. I expected there's going to be at least 1 highly correlated variable that contributed to the infection rate. It's still a good project though

Good, but had some problems when working from my computer directly, I worked on my PC using pycharm and had some trouble finding some misiing code lines that shows the graphics made in the project. But besides that little problem, the course was very nice and good :D

Good Coursework. Some concepts covered are around basic data structure manipulation like loading data into pandas, aligning axes, joining two datasets. Rest is around visualization techniques using seaborn at a basic level. Overall a good beginner level course.

Thank you for the course is clear and slow fits the beginners' need, but there are some some steps lost and some of the contents are outdated. Yes, to research the lost/ outdated part is good for the memory, still, some updates would be nice.

COVID19 Data Analysis Using Python is a great course! Some essential data analysis topics/math concepts are glossed over, but as long as you are using this as a supplement and not a primary resource, you will be fine. Highly recommended!

Well structured, easy to understand and step by step guide. I really enjoyed working on this project. If one graded practical assignment is included in this project, it would be much better.

I had a wonderful experience in this course also I'd love to learn more from the instructor as he explains everything so well that a rookie can start without fearing anything.

This is very good this can help me in my personal project and my analysis in Data Science thank you coursera offer me this project as well as instructor of this project

I like the course as a quick introduction to data analysis. Completion of this project was so fun as i took only couple of hours. I am satisfied with this course.

The instructor's informative videos along with the facilitation of real time application of methods learnt through Rhyme made this a really worthwhile project.

I really enjoyed this class. The only problem is the application used which is not very practical. Kernel is slow and it's very complicated for Mac users.

I found the instructor very helpful and through with the concepts. Would love to join another project with perhaps more advanced data analysis .

Good experience with beginner-friendly design, although some of the misspellings on the instructions in the notebook were annoying

If You are new to data Science, This course will help you to understand Data manipulation using Pandas,and also plotting them

Included real world dataset, but the statistics part could have been much better other than just pandas corr() function.