It would be better if for each function there were more examples.

Average. Not useful even to tackle its own quizes and assignment.

Explanation could be more elaborated like the earlier courses

Not well explained.... Previous module was better structured.

Useful.

Too much talking. Not enough integrated exercises.

Mostly just R programming with data science in passing.

Very usefull but can be technical and discouraging

needs little more real time scenario examples..

Course is too simple, should be more extensive.

peer review assignment is not getting reviewed

practices is much needed to complete projects.

Amazing, Kindly update the versions always.

I THINK THE COURSE NEED TO BE UBDATED

It needs an update on some libraries.

Useful, but a little boring.

its so hard for beginner to

Interesting but too simple.

Sometimes is hard to follow

The assignment was tough.

A little hard to follow

Too much repetittion.

Too tough

Professors did not do a lot beyond rehearsing what the commands did. More important, there were a lot of small things that would stop progress on the course unless you went deep into the forums - for instance, one of the files in the final project was illegible unless you used the right text editor. Final project was poorly designed in that the data were untidy but intended to stay that way (See "Should I decompose the variable names?" in Thoughtful Bloke's post at https://thoughtfulbloke.wordpress.com/2015/09/09/getting-and-cleaning-the-assignment/ - he is right about jerk and mag but wrong about time/freq, gravity/body, acc/gyro, and x/y/z, which are mutually exclusive members of the same set and thus values that appear in column names). I appreciate that this course, unlike other online courses, actually makes you think, but students should only have to think about topics germane to the course. Overall much more frustrating and time-consuming than it should have been.

This course is poorly structured and unnecessarily confusing for beginners. The instructions often feel fragmented, and many steps are not clearly explained, which makes completing assignments frustrating rather than educational. There is a lot of redundant information and unclear guidance, especially in the programming assignments, where students are expected to follow commands without properly understanding their purpose. This creates a feeling of memorization rather than real learning. The lab environment and file structure issues also make it difficult to focus on actual learning, as students spend more time troubleshooting setup problems than understanding data concepts. Overall, the course could be significantly improved by providing clearer explanations, better step-by-step guidance, and reducing unnecessary complexity in the instructions.

This course is by far the least polished and engaging course I've taken on Data Science in Coursera. It just feels like it's 'phoned in'. Like the lecturer isn't really bothered with making it interesting, and just wants to reel off all this stuff as quickly as possible.

Then there are things that are just sloppy - like the section on Regular Expressions - they cover them, but then don't demonstrate their usage in R even once. Like - what function(s) can I use this stuff in? Then, at the end of Regular Expressions, he talks about turning off the 'greediness' of the * operator, but then doesn't even bother to show what that means via an example. It's like he just couldn't wait to finish the video.

I'm doing this course as part of the 10-course specialisation, but if the next courses are this flat and boring I'll probably pull out.