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

4.5
étoiles
7,938 évaluations

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.

DH

1 févr. 2016

Easy, mostly instructive Course. The Assignments and quizzes are quite good, and illustrates the lessons very well.

See the videos for general presentation, but use the energy on the excersizes.

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276 - 300 sur 1,278 Avis pour Obtenir et trier des données

par Patrícia A F

6 avr. 2019

Great Course for you to learn in more detail how data processing works in Data Science.

par Rimi Z

22 juin 2018

A great course and you learn exactly what the title says . I found it fun to work on It

par Tine M

14 nov. 2017

Great course, I've learned a lot about analyzing data sets and creating tidy data sets.

par Robert K

1 mai 2017

Fantastic! I find myself using the information I learned in the class on a daily basis.

par Boris B

6 févr. 2016

Great Course if want to know what data really is and how to handle it in the right way.

par Maxim S

26 août 2020

Thanks, this course was great. It gave me enough knowledge and motivation to go forth.

par Alia E

27 févr. 2017

Wasn't excited about it. But I've used and re-used the materials for work. Good stuff.

par Tseliso M

2 févr. 2017

Of the courses I have done so far in the specialization, this was the most practical.

par Carlos M

2 févr. 2016

Very interesting material and basic knowledge on R to read files and produce tidy data

par GAGAN G

14 oct. 2020

Very nice courses in coursera and fundamental concept are very helping for us. Clear.

par Tomas M

22 août 2017

Excellent course mates! Lots & lots of very useful info & examples! Thanks so much!!!

par Dmytro I

15 mai 2017

It's a great course, however, explanations to the final assignment were rather vague.

par sambit c

12 oct. 2016

A great course. Learned a lot. However student has to put an extra effort practicing.

par Kseniia K

3 mai 2016

Great course, more difficult than previous two, but also more challenging and useful!

par Wang J

1 mai 2016

Great practice for R programming and the MySQL part is extremely helpful for my work.

par leo n

8 août 2019

This is the best course so far. Very challenging project at the end. I learned a lot

par Jorge A B J

25 juil. 2019

Very nice course! Would defensively recommend to anyone seeking this specialization!

par Puja G

6 févr. 2018

Very useful to get hands on experience in data science to solve real world problems!

par Stephen A

3 oct. 2020

This course gives all necessary foundations to kick start getting and cleaning data

par Abay J

20 janv. 2019

Love quizzes and a course project. Working on them develops you as a data scientist

par Ajendra S

29 août 2018

I really liked this course. This course helped me to understand the data wrangling.

par Tiago P F

3 janv. 2018

Excellent course, with a very important focus on documentation and code versioning.

par jutzhang

26 juin 2016

建议更新课程中所涉及函数的使用方法

Please update the using methods of some functions in this lecture.

par Andaru

12 févr. 2016

90% of data science is cleaning, this really gets people accepting that key concept

par Luz M S G

29 août 2020

It was an excellent course. It was challenging but I enjoyed it and learnt a lot.