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.
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.
par Johnnery A•
22 sept. 2019
Los profesores debe explicar con mas detalle los temas. Pienso que hay una brecha importante entre los temas del curso y los proyectos
par Jose L S V•
1 mars 2021
Muy buen curso, pero a veces batallas con las tareas. Toma más tiempo del que se supone debería. Aún así, lo recomiendo ampliamente.
par harish s•
26 déc. 2020
good course. swirl rules!. I think the unique part of this course is the assignments and course project, they are quite challenging.
par kipchumba B•
28 févr. 2021
It's a nice course. Prior to starting this course, I knew nothing about getting let alone cleaning data. thanks to JHU and coursera
par Ricardo M•
8 nov. 2017
Assigments description should have a clearer description. In some cases it's not absolutely clear what is intended to be delivered
par Karolina W•
12 juin 2016
Good course, learned a lot especially through the quizzes and the course project, but slides/presentations could be more engaging.
par Hernan S•
15 avr. 2016
Fun and interesting. Won't remember all the ways to get and clean data, but it's good to review them so I know what's possible.
par C. T M•
27 janv. 2016
it's a little rapid fire, but the exercises are excellent for applying the firehose of functions and concepts from the lecture
par Irmgard T•
20 juin 2017
Good course, though I found that the lecture content could have matched the knowledge required for the tasks/projects better.
par Md F A•
23 mai 2016
The demanding complexity for 'programming-project( final )' should offer little more instructional support on lecture slides.
par Alfredo A•
12 juin 2017
Great introductory course in how to use R to get data from different sources and leave record of this step of data analysis.
par José I F J•
17 nov. 2016
It is a very good course, but it does not follow the same level of proposed work as in the previous course (R Programming).
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.
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.