R Programming introduces many useful concepts and skills to learner in the first stage like me. During my study, course forum and the "swirl" package played very important roles. I am new to the R language, thus the assignment after the course are difficult for me. Thanks to the course forum, I learned a lot from others, and the "swirl" package helped me understand some course more efficient. I will keep on going at Coursera, thanks for the teachers and classmates.

课程比较多的讲述了R的基础知识，这是什么不会搜什么的学习方式所不能带来的。希望课程能增加一些更有趣的作业。同时，短时间内接触大量基础知识容易感到枯燥并且难以牢记，建议每一个视频后面增加短短的几个编程的习题，这样可以更快地掌握。

The course is more about the basic knowledge of R, which is good considering that looking for the answer when meeting with problems cannot teach this. Hope that more interesting assignments could be added. Finally, too much basic knowledge makes people boring, it would be better if after each video the students could do some short programming tasks.

Lectures should include examples of problem-solving and debugging related to the assignments. Every new concept/function introduced should be exemplified on an R dataset. Don't leave it all too swirl. Assignments should not introduce new concepts. Very useful would be examples of script optimization. I spent 90%of the time figuring out what was wrong with my script, and 10% on lectures, which were not clearly explained and very often were hard to focus on.

A quick warm up course for new learner in R. I spent a week to went through the course material and most of the experiment/programming tasks. Now feel quite comfortable to basic R. The course might be improved if more time are spent on some concrete case studies. Some useful functions/routines like str, csv header preprocessing are very handy and it is great to learn these. The last part, debug and profile seem not big concerns for new learners.

The best part of the course is it's assignments which help us enormously to cover up the topics which we have learnt so far in this course. But the biggest downside is the toughness of the assignments which makes the life of a simple student horrible. We have to consult sources outside of coursera to complete them which i think should be covered up well by the lectures in the series.Otherwise the course is a great headstart for beginners.

The course is very well laid out to demonstrate the main features of R programming language. (To elaborate on one thing that I liked) The programming assignment for the 4th week (rating/choosing hospital based on outcome) is very helpful to try out what I learnt from the course so far. All the 3 parts of this question are connected well, and I hope the rest of the courses of the Data Specialization is also implementing similar format.

R Programming has solid information and exercises on just that! However the videos and sections for each week are not very clearly structured. Sometimes the end assignment can take many times the number of hours the rest of the content in a week requires. I'd be careful about taking this course while working unless you can devote serious time to programming projects on your off days. That stated, the course is excellent otherwise.

Very good course; I would give it 5 stars if the lessons would include more examples of how to apply the functions and programming techniques learned in different situations or data sets, before que programming assignments. The current lessons show very basic examples and leave a lot open for one to figure out on your own, I know you're trying to encourage self-learning, but still... Right now this is rather some 70% self-learning.

Overall course was good. I think there is a bit of a gap in terms of helping providing additional understanding of application of some the concepts in context of a solution. I think the course does a good job explaining the concept, but I feel the course could use some additional examples of application of the concepts to help facilitate the programming assignments. The Swirl exercise are good...but almost seem to rudimentary.

I really enjoyed this course, however I have 2 main gripes; 1. The whole process of pushing to github is not very well explained and although if you search in the forums you will eventually find a solution that works, it was still a pain. 2. I loved creating the functions very important, however I felt the material was very light. Too bad Roger and team can't update this course. It is really beneficial to the overall program.

The course was interesting, nevertheless it required me to spent many hours thinking to approach assignments which seemed to somehow tricky. fortunately there was an extremely important and vibrant discussion forums created for students to refer to while approaching those assignment. I recommend every student to read the discussion forum, especially when one is confused on how to do the assignments. otherwise, thanks a lot!

Iam I student having background from biology. Programming was totally new for me. The course was very beneficial and we'll arranged. The assignments and quizz were very demanding, but if one goes through all the videos, notes and swirl exercise than it becomes easy to solve. I learned may new thing and R programming. But still have have doubts and I'm not clear about applying the knowledge of R in the field of biology.

A little bit more examples, as well as maybe a walk along with example where the students works an example in R-Studio, and can try to answer some questions, one screen before the answer is given. I had some problems that didn't know about until I was taking the quiz. Other than that I really liked the course and am looking forward to using this knowledge as well as the Getting and Cleaning Data in the real world...

Very good course. The swirl (optional) exercises are a great tool to apply the learning of each week right away. I had no prior experience with R and very little with programming in general ; I spent a lot of time looking for the right functions, their arguments etc. + debugging my own code because of all the rookie mistakes I make ;) But practice makes the master, so I guess it's normal.

Now off to the next course!

I highly rate the course, the material, and the instructors. I only have one concern, which is the gap between the weekly course materials and the final assignments. I understand that in areas like data science, the learner should go beyond the course materials, but I think either course materials should have been more challenging, or the assignments be more based on the subjects covered during the week.

Thanks

Good course for a determined person! There is a very big gap between the course materials and the later assignments. I wish the lecture slides were available for quick reference, but you only get the transcript of the words the lecturer says or the video itself. There was a bit of a leap when the various statistical distributions were referenced with the presumption the student knows what they are all about.

This course is really not easy to who is not in the domain of computer science. Even the computer science people, it's also not quite easy to familiar with that statistic program, e.g. R Programming. If having more "trace program" training, I'd be better for that students who I mention above.

However, anyway, I very much enjoyed this course to know how to program to analysis a data set.

Thank you very much.

Good course in general. Gives a introduction to R and its basic function and structures. I recommend this courses to the ones who start using R as an analytical tool and have some basic experience with programming or data analyses. Maybe some improvement would be nice: For example, some of the assignments weren't fully consistent with coursework. However, overall a great introduction to R programming.

This course is essential, thus, it is imperative that the concepts are well understood by the students. More emphasis on the underlying logic, rather than the syntax is very welcome.

For the succeeding courses, R is going to be used anyway, so familiarity on the syntax would come naturally. The "how to make it work /why doesn't it work" is more beneficial than "what do I need to use", I think.

Swirl is very good. it would be good if it detected differences in input for a typo error, compared to a guess, and also if it ignores results if the expected outcome is achieved e.g. sqrt(x) and (x^0.5). i'm sure a clever identical() function in there could produce a responsive feedback like. "OK, not quite what I was thinking, you should have type sqrt(x), but you seem to have managed to get t

For a beginner like me, this course is really helpful. It gives valuable certification and builds your knowledge in statistical programming. Though the lecture videos could be a bit more interesting but nevertheless it helped big time. The assignments lets you think analytically so as to arrive at the desired output. It's a great course for people trying to place their foothold in data science.

I only finished week one so far. My opinion (to the first week's content) is that it's a little bit hard to familiarize all those basic R concepts from scratch. Maybe the teaching staff would want to make it more concise so that before any real application (or simulation), students do not get lost in those technicalities. However, it's pretty great course. It's pretty detailed and informative.

If you want to learn R for real take this course. But !! keep in mind this course is not for the weak of heart.

It is not a hand holding class. You will have to dig deep inside your soul to come out on the other side alive. But when you do, you will have emerged Victorious. And walk away with your head held high and say " YES, I am an R programmer!"

good luck may your kung-fu be strong :) .....

Course was great! The challenge level was good for me, although some of the assignments introduced concepts that wern't covered in the swirl or lectures.

I'm used to assignments driving home lecture and problem concepts, so I think that mentally I wasn't prepared for the introduction of concepts for the assignment. I think that if this knowledge gap was solved, the course would have been a 5.

Actually, I was surprised by lesson 3, it is more difficult that lesson 4. If someone has no experience in programming, especially in R, there is a good chance of failing the assignment. If the instructors can include more useful functions in the course, I think will be excellent. Especially if they can give an introduction about the other relevant packages in R, it will be extremely useful.