The length of the course, in my opinion, is a little bit too long. Actually it took me only 3 days to complete this course and I am not really a brilliant one. So I think maybe may will have the same opinion.

Not a bad intro; I don't know if anyone would benefit taking this as a standalone (or for an entire 4 weeks, for that matter). Still, it introduced some solid concepts for professionals and scholars, alike.

Though the content of the course is nice, i wasn't completely comprehend everything. I was expecting to see a lot of explaining using the live screen mode, i.e., explanation while operating on the desktop.

This is a really basic course. If you have never touch code before, it's more useful, but little is actually covered here and the gap between it's contents and the next class, R programming is dramatic.

Super basic, each week was only about 30 minutes of video lecture... but I think that was their goal? Bad form on coursera for making you pay to submit assignments that are autograded to begin with.

This is a required course in the Data Science specialization. If you're planning to take that specialization, you should start with this course. If not, you shouldn't bother - there's not much here.

As a software engineer I found this course a bit useless, but I do understand other people don't have the same background. Having said that, I believe it should be optional in the specialization.

It's a great course. But the peer-graded setting of projects really delays the grant of certificate. It took me more than two sessions of waiting just to get a grade for the peer-review project.

Very basic, can be done in one day! However, we always need something simple to begin learning something new. Also, it was useful to have some guidance in the installation of the various tools.

The course is basic, and quite simple. Some might say too simple. I think it should be about 1 week long. I already knew all the things going into it so it was easy to finish it over two days.

unforutnately automatic video are quite hard for non native speaker. You always need to revert to reading material

the intro to R should be extended with more practical exercises and examples

The theoretical part of the course is good, but the quizz questions were simplistic and very hastily prepared. I would recommend this course as an optional module and not as a graded course.

I like to continue, but i stopped learning because the robot instruction which is annoying presentation.

I'm looking other courses which has better presentation tools, like real instructors.

It's a very basic introduction. Would be nice to have the option to skip it for more advanced students.

Also the recorded lectures are really quite, so you have to turn up the speaker a lot.

Good Introduction to the basic tool set, Can be bit more comprehensive by giving an overview of other tools available to do the same operations and also why this tool set has been chosen.

There wasn't much to learn that I didn't already know. There was a lot of talk but no real practical application (I guess except for github for people that didn't know how to use that).

This course coud have been provided as intro to R programming course or it could be just planned for 1 week. Anyway, overall it was ok though not yet extremely intense or informative.

It was a good overview. I understand that it’s really just a quick intro into upcoming specialization courses. I wouldn’t take it alone. But I’m excited for the rest of the courses!

I got a brief understanding of R. Better something than nothing. The problem is, they need to update their lectures. This would be less confusing and more convenient for students.

I know it might be the future for training videos but had a hard time staying concentrated listening to a mono tone computer generated voice. The course content itself was good.

Make it more illustrative.. The examples are very less and not explained properly for beginner. Assignments should be more practical. There must be a tutor to clarify the query.

A good attempt to give introduction on basic Data Science tools though most videos end abruptly which spoils the seamless navigation experience. Maybe the team can work on this.

Good introduction, but the professor could have been more descriptive about how to use git/github. These are new concepts for people so it may be difficult to grasp right away.

Course content is decent but needs to be simplified little to advance if dont't have previous programming experience. Robot voice is annoying would have preferred instructors.

Probably a good course if you aren't terribly familiar with GIT or some form of version control. It also helps to get all the tools in place to be ready for the other courses.