May 03, 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.
Oct 26, 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.
von Fabiana G•
Jun 23, 2016
The content of the course is good, but it seems abandoned - some links are outdated or don't work. I think it would be a much better experience for students if these first courses in the specialization got more love from the instructors.
von Steve W•
Feb 03, 2016
The lecture material was high level, and didn't seem to be a good preparation for the quizzes.
The description for the final project was not very detailed, and the grading rubric likewise was not very specific for peer review.
von Andrew G•
Jul 28, 2018
I thought the course project grading was supposed to focus on what we learned in class, not almost entirely on creating readme and codebook files. Also, the explanation of what was expected for the project was NOT CLEAR,
von Wentao B•
Apr 03, 2016
The content of the course is too general, with too brief introduction of some commands in the lecture notes(slides), I don't think it would be very helpful for the students to deal with some real complicated problems.
von Justin z•
Apr 13, 2017
brought up some good concept inside, like "tidy data", but not in detail, how to grab data from different source shouldn't be difficult. should have more focus on talking about data.table, "tidy data" principles etc.
von Bekhzod A•
Mar 13, 2016
Course provides interesting insight to getting and cleaning data. However, the course misses practical examples (not only showing the code in the slides, but also presenting how it works in R or RStudio).
von Ehab H A•
Feb 05, 2019
This course was too hard for me compared to the first two in the program. Not sure whether it is because of my limited background in the subject area, or because of the abrupt shift in level from course 2 to 3.
von Sven B•
Apr 30, 2016
This course is of lower quality than the preceding courses. The final assignment instructions are not clear. The forums helped but I have the impression that they are not really followed by the mentors.
von Pedro R A O•
Sep 10, 2017
the course is good in terms of the knowledge but it is very unstructured. A lot of topics are treted just superficialy and the activities do not address the content of que lectures completelly.
von Rigoberto Á E•
Nov 27, 2017
The professor Leak is not as gifted (in terms of teaching skills) as R. Peng. In some of the lectures he just reads what it's in the presentations but he does not go very deep into them.
von Deleted A•
Aug 13, 2016
Contents in first half weeks are very superficial, have low depth so that do not help me do some meaningful studies. But later ones are good for understanding the structure of data.
von Shuwen Y•
May 28, 2016
less hands-on exercises and this course covers too much topics without details. More like general intro to each tool and data sources. Swirl is still a great package for practice.
von Christoph G•
Jun 12, 2016
I liked it, but I had the impression it wasn't as prepared as the other courses. Especially with the course assignment I had a bit trouble to understand, what was wanted.
von Angela L•
Jan 20, 2016
This is not a beginner's course, so a decent grasp of the R language is necessary. It is best to take this course after some stints with Data Camp, Swirl, or Code School.
von Yuqi J•
Jan 14, 2019
Some of the lectures on loading data were very dry, but I guess that can't really be helped. Also the final course project's requirements were on the vague side.
von Samantha H•
May 31, 2018
It would be better if we had practice problems along the way. This course seemed to have a lot of commands that didn't stick until I put them into practice.
von András H•
Mar 04, 2018
This is an important course, but many updates will be needed. There are only a few exercise task, there could be more. The swirl part of the course is good.
von Andrew C•
Sep 21, 2016
The best course so far (though that's not saying much). This course would be better as a follow up to an example workflow showing an end to end analysis.
von amir a s•
Mar 08, 2020
Not on par with the course sets before it, could have been a bit more explaining as cleaning data is one of the most important parts of data science.
von RAMANANJATO R H•
Jul 06, 2020
The content of the course is very interesting and useful. However, I found very challenging the difference between lectures and quizzes/assignements
von Bijan S•
Jan 30, 2016
The selection of topics is great. However, the course is too abstract. I think some of the materials deserve to be discussed more comprehensively.
von Paymon H•
Apr 14, 2016
Toughest class in the offering. There really could've been 2 classes for cleaning data. I struggled with the lecturer's style (spoke too fast).
von Daniel D•
Sep 03, 2019
The project description could have been a lot more descriptive for what we were supposed to do. Otherwise, I had a lot of fun with this section.
von Teodor I•
Jan 09, 2018
The non-clickable links in the pdf are a major problem. You need to figure it out. Create a link reference field for each video or something.
von Nishi G•
Apr 27, 2017
To get value from the class, I used other on-line materials to understand the topic. Thus, I spent about 20 hours/week on this class.