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Avis et commentaires pour d'étudiants pour COVID19 Data Analysis Using Python par Coursera Project Network

4.5
étoiles
1,903 évaluations

À propos du cours

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....

Meilleurs avis

RP

27 juin 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!

DD

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 sur 380 Avis pour COVID19 Data Analysis Using Python

par PAVAN K A

13 juin 2020

good

par Kammari K

12 juin 2020

good

par Gaurav K

11 juin 2020

best

par Ashwin P

4 juin 2020

good

par ABDULLAH A N

26 juin 2020

wow

par Trisha H

1 sept. 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

par Guo X W

4 juin 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.

par Sori K

11 août 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...

par Azzahraa A

2 juin 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

par Karen L B S

19 juil. 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

par Suyash C

21 juil. 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.

par Stephanie E

17 août 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!

par Uzair H

26 juin 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.

par Rupesh S

11 juin 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.

par KHALID U

31 juil. 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

par sunney U

16 sept. 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.

par Hareesh S P

6 juil. 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.

par héric L

24 juil. 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.

par KAPIL S C

18 juin 2020

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

par Davy Y

3 févr. 2021

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

par Aman A

6 juin 2020

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

par Mohammed N H

16 déc. 2021

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

par Kamrul I M

26 sept. 2020

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

par xinran C

21 juin 2020

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

par Steven O

18 déc. 2020

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