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.

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.

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.

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.

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.

Some lessons are pretty good, but there is a gap between the lessons and the assigments. You're evaluated in some aspects that are not very explained in the lessons.

Assiignments are out of date, some commands are deprecated. Also, the quizzes and projects require more in depth lessons or practice problems to complete. Thank you

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.

I think this one is easier than the R programming but still, more exercises to practice would be good. Also, the assignment's explanation should be more simple.

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.

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.

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.

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.

The content of the course is very interesting and useful. However, I found very challenging the difference between lectures and quizzes/assignements

The selection of topics is great. However, the course is too abstract. I think some of the materials deserve to be discussed more comprehensively.

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).

Some assessments are not well related with topics developed during classes. Then, it is difficult to understand what it is the goal to achieve.

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.

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.

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.

I felt I had to teach myself in this course. I feel I would have had the same learning experience if I had purchased a good R book.

A lot of things covered in this course in a short time. Probably should have been 8 weeks with more homework done step by step.

great materials but unrelated to assignments. great real life experience "here is link. make it nice. deadline yesterday"

Sometimes I felt the were not evaluating my learning or ability to do things but my ability to read instructor's mind.

it gives us good information, but the information sometimes are incomplete or need to be updated( created in 2014!)