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.
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.
par Francisco J D d S F G•
3 nov. 2016
A thorough course on how to structure and clean dirty data before making analyses on the data - very practical course in R.
par Rejane R d C P•
2 nov. 2020
I think some assignments may be more clear such as the final project. They give way to several different interpretations.
par Greg R•
14 avr. 2016
Some parts of the course felt like... here are some cool things you might want to do... Google them. Otherwise valuable.
par Lei S•
24 déc. 2017
A little bit hard to follow, because there were so many things didn't work for me. I had to figure things out by myself.
par Madhav S K U•
29 mai 2017
i found this useful and gained knowledge on important pacakages,if you are a beginer in R do not skip "swirl " practice.
par Jeroen v B•
16 sept. 2018
The course is ok, but a little bit too general. It should require more actual coding, maybe worksheets might be useful.
par Giovanna A G•
25 sept. 2016
It is amazing to learn how many different kinds of data exists and how to work with them using R. Wonderful course!
par Tran H H T•
21 févr. 2016
Slides and videos are a bit insufficient in order to finish course projects.
Apart from that, this course is awesome!
par ESTEBAN C P•
23 août 2021
Definetly it´s a better than the 2nd one (R Programming). Hopefully the next one keeps with this didactical level.
par Dylan P•
21 avr. 2018
I think there should be more graded assignments. The quizzes help but doing more projects would be really helpful.
par Tony S•
10 déc. 2022
Quite a leap from course content to final project but still a rewarding course with lots of hands on coding in R
14 août 2016
I think it is a decent introduction to data cleaning. Could be more detailed in terms of the content delivered.
par Matt C•
22 déc. 2016
This course was okay, but projects required much more in depth information than the course materials provided.
par Edén S•
4 juil. 2020
Very interesting course where we learn the methods to get data from the web, clean data and getting it clean.
par EzzEddin A•
22 févr. 2018
This course is brilliant, but I expected more exercises to master more commands in R mentioned in the course.
par Stephen K•
8 avr. 2017
Great info on accessing data from multiple sources. Also some excellent teaching on relevant R code modules.
par Thiago Y•
30 août 2020
This part of the specialization is very important since 70% of a data scientist work is get and clean data.
par Nikita Z•
21 mai 2020
I tried my best to the best, certain things were little complicated to understand but it was worth learning
par Agatha L•
16 août 2017
The content choice is fantastic - introduced a lot of great tools - albeit somewhat rushed in presentation.
par Gianluca M•
16 févr. 2017
Very good place to learn very important tools like dyplr and tidyr to access and clean from several formats
par Sharon A•
15 avr. 2018
Allows you to deepen your knowledge in R how to get data. The final work was challenging, but possible :-)
par Blazej M•
12 nov. 2017
Nice course. Far easier than R-Programming. Could be refreshed to match tidyverse workflow. Otherwise OK.
par Dimitris A•
30 nov. 2018
The assignments are sometimes poorly explained. Other than that this is a solid and very useful course.
par Marcel A G•
8 nov. 2018
It was a great course, however I had a bit of confusion when trying to understand the final assignment.
par Tri B•
1 avr. 2022
This course is quite challenging but it provides me basic idea of tiny data which is very helpful.