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Bewertung und Feedback des Lernenden für COVID19 Data Analysis Using Python von Coursera Project Network

1,903 Bewertungen

Über den Kurs

In this project, you will learn how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consist of various life factors, scored by the people living in each country around the globe. We are going to merge these two datasets to see if there is any relationship between the spread of the virus in a country and how happy people are, living in that country. Notes: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....



27. Juni 2020

This course is very good for beginners, although it misses out a lot of points in terms of professional data analysis...

Still, if you are a beginner, you will benefit a lot from this course!


27. Nov. 2020

i guess it is a fun course ad very easily managed via rhyme notebook. i guess anyone with interest in data science can come here and catch some curiosity or understand what they need to learn.

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251 - 275 von 380 Bewertungen für COVID19 Data Analysis Using Python


13. Juni 2020


von Kammari K

12. Juni 2020


von Gaurav K

11. Juni 2020


von Ashwin P

4. Juni 2020



26. Juni 2020


von Trisha H

1. Sep. 2020

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

von Guo X W

4. Juni 2020

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.

von Sori K

11. Aug. 2020

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...

von Azzahraa A

2. Juni 2020

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

von Karen L B S

19. Juli 2020

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

von Suyash C

21. Juli 2020

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.

von Stephanie E

17. Aug. 2020

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!

von Uzair H

26. Juni 2020

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.

von Rupesh S

11. Juni 2020

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.


31. Juli 2020

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

von sunney U

16. Sep. 2020

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.

von Hareesh S P

6. Juli 2020

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

von héric L

24. Juli 2020

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.


18. Juni 2020

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

von Davy Y

3. Feb. 2021

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

von Aman A

6. Juni 2020

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

von Mohammed N H

16. Dez. 2021

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

von Kamrul I M

26. Sep. 2020

One star is not given because of the cloud timelimit. I think the project could be taught via non cloud platform way.

von xinran C

21. Juni 2020

The project os compact and merge programming with analysis, but it's easy if you have python programming experience.

von Steven O

18. Dez. 2020

good introduction, it would be helpful to know the source of the data used so we could do our own analysis