Need to have more visual approach to the course.

The swirl course is very helpful.

Good course

Nice!

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The forum for the final week has everyone asking each other to review their assignment because it doesn't get done. There might be something broken with the system here.

With regards to content, it would probably be better to just read Hadley Wickham's "Advanced R", and "R Packages", and "ggplot2" for this whole specialisation. In fact, I wouldn't be surprised if the material for the specialisation was just taken from these 3 and "R for Data Science", and then compressed to make it easier to digest in 4 week chunks.

It was ok, so I'll give it 3*. But there could've been more material here. It didn't feel "Advanced" to me.

Like the first module in the specialty, this one is riddled with typos. Some of the examples could have been a little more detailed or just more examples given. Again, some of the swirl assignments were just walking through the readings. The topics covered here are more advanced, but I feel like I just read an online tutorial and didn't really take a "class".

The quality and the difficulty of this course is really good. It would even be better if more advanced topics are covered in details (e.g. AST, substitute function). However, the peer review assignment could be a pain since sometimes you do not get helpful feedback. Occasionally there are not even enough students to grade your assignment.

The content of the course is really good and I learned aspects R programming that differ from what I use in my job on a daily basis. However, my rating is lower than it would otherwise have been due to the peer review part as there seems to be a slow flow of learners and consequently long waiting times for the grading.

This course was not great. Almost all of the information is a screen scrape from a book and peer-evaluation, so you may be better off just getting the book and going through it. The mentors very occasionally participated, the authors never. The assignments are poorly written and missing too much detail.

This feels like self-study rather than being taught.

Despite the reading material is self-contained and well-organized, peer-graded assignment doesn't look good, though.

Getting attention for it to be reviewed is a hassle.

WIsh there were more assignments. The final project was the only assignment in the course. Object-oriented programming in R requires more than a single assignment to grasp- even at a superficial level.

To complete this course you have to go back and forth for the basic. Also the final assignment is bit ambiguous, more clarity is required.

It is a very good course but many a times the concepts which are used in assignments are not even taught properly in the course.

In comparison with the first course, it was not so useful. The main reason in my mind is that there was no video.

The style of these courses is not engaging. This is self study, similar to getting a book and reading.

Being a user that is familiar with Datacamp, there are many frustrations in this course . This is not necessairly built to be self paced. First the way deadlines work and are graded is frustrating. WHile some people reviewing my work commented that my work was impressive, it can take a lot of time to get your work being graded. When you are stuck somewhere, this is not a classroom setting where you can deepen a subject and get to understand. It is especially true when the explanations are relatively shallow. I had to go back to a datacamp class to fully understand object language programming. I feel I have lost a lot of time not on the learning part but on accessory items that related to the way the class was structured and how it was working.

The project object oriented programming was uninspired to say the least. Creating a special class for "Longitudinal Data" seems to me a pointless exercise since a simple dataframe with a column named "time" or something to that affect would suffice. Also, regarding the benchmarking portion of the project, the description of the file factorial_code.R to be submitted was obviously copy/pasted from the OOP portion of the project as it nonsensically refers to "Longitudinal Data". It's easy to spot the error, but you really need the correct text in order to fully understand what you're supposed to be submitting. I submitted blindly and got credit.

The textbook is useful and worth it for $10, but has a lot of typos.

I found this course a bit disappointing. There wasn't much content, no lectures or anything, it was just the book copy-pasted into a course. The final assignment was rather vague, and the course materials didn't prepare you quite enough for it. The peer grading was frustrating and took multiple days of waiting. This is especially annoying in a course where the payment is on a monthly basis: waiting for your grade might mean you have to pay for another month of subscription. I'm cancelling the specialisation and continuing on my own after this.

This courses touches many interesing aspects about R programming but I did not like the structure , it does not seem to me that it adequates its difficulty coming from "The R programming enviornment".

Also I miss some swirl lessons for many of the readings from the book. There are not too many help from the mentors and the peer assigment in week 4 took me too much time and had to consult a lot of external resources. Readings in general are OK but too simple.

I have learnt many things but

The topics are good, but very little practice of creating classes until the final quiz, which expects you to understand it completely without having done any practice.

The Object oriented programming section did not provide an adequate amount of support for the assignment, compared to any of the other parts of the Course.

just links to a webpage... no support from the mentors no support form coursera... you can use your money more wisely..

A bit too tough with not good enough teaching to truly understand the course

difference was observed in final test and study material.