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Avis et commentaires pour d'étudiants pour Obtenir et trier des données par Université Johns-Hopkins

4.6
étoiles
7,863 évaluations
1,288 avis

À propos du cours

Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data....

Meilleurs avis

HS
2 mai 2020

This course provides an introduction of some important concepts and tools on a very important aspect of data science: cleaning and organizing data before any analysis. A must for any data scientist.

BE
25 oct. 2016

This course is really a challenging and compulsory for any one who wants to be a data scientist or working in any sort of data. It teaches you how to make very palatable data-set fro ma messy data.

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101 - 125 sur 1,251 Avis pour Obtenir et trier des données

par Eduardo R R S

9 avr. 2021

es muy buen curso recomendada al 100% la ruta solo que siento que deberían hacer una introducción, a purr ya que los bucles de este paquete de tidyverse son mas efectivos que algunas de las funciones que enzeñan.

par Angie M

19 juil. 2020

One of the most useful courses I've taken so far in Coursera from a beginners perspective. The course does need some updating but overall I was able to complete the assignments with the information provided.

par Francisco M M

20 oct. 2017

Me pareció un excelente curso, muy didáctico y con mucha información adicional para poder estudiar por nuestra cuenta para lograr una mayor profundidad en algunos temas en especial. Lo recomendaría sin duda.

par Nikolai A

3 oct. 2017

I really enjoyed this class. Cleaning data is not very difficult, but it is a very important aspect of Data Science. This class taught me the importance on making data easily readable on top of the process.

par Herson P C d M

6 déc. 2016

Excepcional, estes cursos estão abrindo completamente minha mente para novos horizontes, novas possibilidades. Enfim, estou cada dia mais motivado e mais entusiasmado com tudo de novo que tenho aprendido!

par RONAL O R G

24 sept. 2020

It´s a good course to learn how to sort and get a tidy data, the course project it´s a good challenge but it took time to get the 4 perviews, I think many people have problems with the Git Hub account.

par Nima A

8 juin 2020

A very useful course. The audio quality of some lectures (especially those by the main instructor) was not good. This course completes the sister course of R programming and they work together.

par 현 허

3 mars 2018

I really really loved this course. Some of courses before were outdated because there are lots of changes in packages or others. However, materials in this course were not changed that much.

par Vyasraj V

26 nov. 2017

A lot of insight and practical knowledge of cleaning data that is available in many places in the Internet. I loved this course and it took me 2 tries to pass the peer graded assignment. ;)

par Anna M D C

2 janv. 2019

It was pretty hard for someone like me who has a weakness in programming but it provided sufficient exposure and tasks for me to learn within my capabilities. I did enjoy its challenges.

par Edwin R V C

7 mars 2016

Excellent course. It helps to complement the knowledge of data analysis. The project was quite interesting and illustrative, especially considering that they were real experimental data.

par Vincent B

5 nov. 2017

Very good course! It is a topic which is very often underestimated and we all need to learn to get more productive on this, as most of the time is spend on it in the "real world".

Thanks

par Gianmarco P

3 mai 2020

Very well done. Clear example and balanced explanation. Big advantage if you spend more time looking at the suggested readings. I found usefullpeer- review thanks to other students.

par Balaji P

4 févr. 2018

The course is an excellent introduction to the dplyr package and string manipulation in r. I thought the assignment at the end of the course was a little vague and hard to understand

par B S

14 nov. 2017

Great course if you are working with R. I learned how to load data in R and various handy features (plyr, dplyr, lubridate packages) to clean data before starting the data analysis.

par BOUZENNOUNE Z E

3 mars 2018

Amazing, you get to see almost every aspect of data science.

It is true that you won't get deeepeeeer, but this course allow you to not fear any kind of data science. That's amazing.

par Andrew B

16 oct. 2017

This course is very enlightening. The techniques demonstrated in this course are critical for gathering raw data from various sources and turning it into useful data for analysis.

par Kelly S

22 mai 2019

I really liked this course and believe that my work, although seemingly noob-ish, will get much better as I see others works from the peer review and examples noted in the lessons.

par Sudhin B

17 mars 2018

So knowledgeable and interesting course. I have learned much about data cleaning and getting from different sources. Finally thanks to coursera team for giving us the opportunity.

par Charles K

6 févr. 2016

This is a very well put together course. It teaches the basics of data cleansing and how to setup data for modeling--by far the most foundational technical aspect of data analysis.

par John B

22 sept. 2018

How to get a clean the data is a very important knowledge for the future data scientist and data analyst. For me this course was very important I very recommend take this course.

par Eugene K

7 janv. 2018

Great course on tidy data. Very useful in understanding how to use different types of data (csv, XML, API) and how to manipulate the data so that you can perform analyses on it.

par Mohammad A

16 juin 2018

Excellent course, and quizzes and lecture were very teaching. But some materials needs to be updated up to date , like subsetting columns in data.table the slides were absolute.

par João F

17 oct. 2017

Great ready-to-use skills for common tasks of a Data Scientist. Lays the foundations for further self-development in the topics taught. Heavy on R. Very challenging assignments.

par Amsalu B B

23 mai 2020

This specific course is good but when it comes to the assignments, it's more confused than the course work and the description of the assignment is unclear too, at least to me.