5+ years ago as a graduate student I took a bio-statistics class focused on analysis of NGS data where we used R to do the statistics required in the homework assignments. In that class we mainly used the built-in functions at the console to calculate things like correlation coefficients, but didn't do much real programming or function writing. I took this course because I wanted a refresher in R and because I was interested in learning more about its programming capabilities. From that standpoint I'm really satisfied with the things I learned, especially given the fact that the course is quite short.

I loved the well-thought-out, tricky programming assignments. At the end, I wish there was an 'answer key' or 'hall of fame' for good examples of solutions to the programming assignments. I understand why they can't do this (oversharing/cheating/watering down the challenge for the next class), but it would be awesome to find out if there was a simpler, more elegant or readable solution. R is full of different ways to solve a problem, so it would help us to 'think in r' if we could see worked examples after we're done. That said, the challenge of the blank page is really where I learned the most.

Although there are significant disconnection between the level of difficulty of assignments and what is taught in the lecture videos, the assignment proves to be very challenging and would make your R programming skills improve leaps and bounds. Whenever stuck at assignments, I often search Stackoverflow for specific functions and would be able to find answers from there.

Overall, I think this course is suitable for learners who have some background in programming, and I would be continuing to take the specialization courses to find out more about the statistical packages of R like ggplot2.

This course provides me an overview understanding of R Programming. The professor not only teaches the important programming concepts but also teaches how to learn R programming well (e.g. how to ask good questions in the forum, how to solve problem via different functions). I think the grading of homework is creative and helpful. When I have to evaluate other people's programming work, I had to understand what's going on in the assignment. The swirl packages and each of the homework are time-consuming but really helps a lot for me to better understand and use the R programming.

It was very informative and understandable. This course seems difficult in the beginning as we need to remember various syntactic notations. When you are in such a situation, don't forget to start using swirl. Even if you are a quick learner of syntax, swirl takes your journey like a cake walk as it just plants all the course content into your brain. It is such an interactive,student friendly environment being provided in the course that it makes you fall in love with swirl, course and instructor's methodologies.I am really thankful to John Hopkins university for such a course.

The video lectures were engaging with interesting tidbits thrown in to make the potentially dull topic not dull. I personally liked the rhythm and pace with which Dr Peng delivered the content. Also, the swirl exercises are a critical element of this course and I often found it effective to sandwich the swirl exercises between the video and the quiz. Doing this provided an incentive to complete the swirl practice and also made the quiz/assignment less of an exercise in 'dart-throwing' and more of validating what you've learned. Overall, great course to get started with R!

Excellent Course in R Programming for beginners and advanced programmers alike. The programming assignments are a bit of a leap from the course material, so be prepared to be a hacker and search for solutions in the discussion forums, and save time for those assignments if you are new to programming.

Most of the theoretical background is not provided and not the focus of the course (such as mathematical statistics, linear modeling, etc), however, the R-programming aspect of them is presented in an understandable way so that the basics come through. Thank you, Dr. Peng.

As a new programmer, I had to chew on this one for weeks and after looping through the video's over and over again eventually mastering it. The swirl exercises are absolutely essential, and so is the discussion forum (and uncle Google / hacking skills). Although frustrated occasionally - and watching others being frustrated or even giving up, I believe the entire course was set up brilliantly. From the assignments I liked the lexical scoping assignment the least. Would have been nice to be replaced by something little bit more encouraging.

I finished this last year with a good background already in R. However, this course took a lot of time, a lot of stackoverflow searching and generally a lot of work! Now that I'm a year removed from the course, I can say that it's been one of the better, more rigorous, more practical and more applicable courses i've taken. I still spend A GREAT DEAL of my time looking for answers online but now the questions and tasks are much more complex now that I've taken my programming skills to higher levels, with lots of thanks to this course!

The Data Science specialisation with John Hopkins University is definitely worthwhile and, as a relative novice in the area, I'd highly rate and recommend R Programming. The lecturer Mr Peng presents the information in a clear and concise way, conducting walk-throughs of different steps, and providing opportunity for practice exercises. As well, the accompanying book published by the lecturer, learning materials, mentor Mr Warren and discussion board are invaluable for beginners like myself. Thank you for a terrific course so far.

Well-organized R programming course for academic amateur with some OOP knowledge before! By simply using Rgui, th is class focuses on techniques in ABC's of R programming including not limited to basci objects, data strcuture, controlling sentences, I/O and debugging suggestions.

Personally, I take this course for job purpose, but this course falls short for industrial techniques, such as reading/outputting excel, sophiticated operation on data frame, or combining R with Python and SQL.

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Lectures are well-presented and programming assignments are engaging (but they took me about eight hours to do each week). Swirl was a great tool for getting to grips with how to use the functions discussed. Definitely recommend having a pen and pad with you to take notes throughout - have no idea how the course could be done without doing this. Overall, I found it an engaging and suitably-challenging course for someone new to R , and with a little tweaking of programming assignment 3, I think it could be an industry standard.

I think making this course self-paced is a great idea. This is a well put together course. My only concern is for those who have not done programming before. Maybe a prerequisite course could be recommended? I recall doing an excellent Python for beginners course recently. Personally I'm not a big fan of peer correcting, I know this is a big part of making Coursera work, but for classes like this one, I think something like SWIRL would work best. Anyway, that was my two cents. KEEP OF THE GREAT WORK, YOU GUYS ROCK! :)

Wonderful course, it forced me to depend on myself. I had to search, I had to read and go through lots of articles, questions, solutions and tutorials online and also, in the discussion board to solve the assignments. I believe it is the best way for someone to get knee deep and learn the language. This is exactly the methodology that should be followed in the real world. One would have to search and find solutions for any issues that are encountered. I enjoyed it and moving on to completing the specialization.

Amazing course! You get to learn the in-depth nuances of R-Programming. Not just that, this course makes you work really hard. You need to troubleshoot your own problems, and you find even better code, a smarter and an even more lean way of coding which is simply brilliant! If you're looking for a course that will help you grasp R Programming, I would strongly recommend going through the entire Data Science Specialization. Kudos to the Coursera and The Johns Hopkins Team for putting up this course together!

It is tougher than it seems. The idioms are R are difficult to master and more time is needed. It is almost as if knowing R is a pre-requisite for this course. The forums were quite helpful. If you spend more time during the week on R and take the same problem and try to solve it in many different ways then you would get more out of it. the lexical scoping, the libraries, the syntax for efficient processing using apply, pipelines are crucial to understand R and not treat it like another procedural language

Excellent introductory discussions in the videos. The in-R Swirl tutorial is superb - a great way to force you to type out the basic concepts. Assignments are challenging as they leave a little ambiguity, making you get familiar with the help system and online searches. This course isn't the fastest way to get an overview of R, but it's a great way to get a little more than an overview, including some practical experience, if you're willing to put in a little time and work through some bumps.

Overall, this course was fairly challenging and at times I would get frustrated, but every minute was worth it after realizing the knowledge I have gained and have been able to use in the real world. I think sometimes the assignments just kind of dive right in and there's not much hand-holding, but that can be a good thing. My only suggestion would be to extend the course from 4 to 6 weeks and spread out the material a bit, but overall, you just have to be committed and make time.

This is a fast-paced and autodidact course. You'll learn in a real life environment (unlike the incredibly boring DataCamp courses). Instead of providing exercises you must be curious and learn and look for whatever you want. The quizzes were always challenging, sometimes going beyond the course material -which is, in my opinion, a great decission-. I learned in a month what I could have learned in 3 or 4 with DataCamp.

I thank Roger D. Peng for making this course possible.

This course is very good for beginners in R language and it is highly recommended for people looking to dive into the world of Data Analytics or Machine Learning. R is very powerful language and this course from one of the reputed universities of the world, John Hopkins is one of the best out there to learn from.

The difficulty level of programming assignments is increased gradually to challenge the programmer inside you. Overall a highly recommended course for beginners.

I really liked this course. He covered the basics of the R program and gives activities with Swirl that help strengthen knowledge. As for the evaluations, the questions are to verify if the basic knowledge has been strengthened, but the assignments are quite a challenge since you are on your own which is frustrating at first, but when everything goes well it is rewarding. However assignments are very time consuming, therefore I recommend the course to people who have it.

Excellent course for beginners of students aspiring data analytics as a career. It teaches us the fundamentals of R programming language with utmost clarity and challenging assignments. The discussion forums were very much helpful. Everything goes smooth if we complete the course within the stipulated time. I had a wonderful experience completing my first course in Data Science and also in Coursera. I'm looking forward to complete more courses and strengthen my career.

Maybe its just me that it seemed the instructor speaks very fast that I have a slow mind to comprehend the instructor is discussing. I really have to pause and rewind just to fully understand the topic. Luckily they include an interactive way of learning the topics via swirl and this is really a good idea. A student like me can immediately applied the lessons in swirl and review what is happening. All in all its a great experience learning this course. Good job.

A comprehensive introduction to programming in R, for people already experienced with numerical software like MATLAB and Mathematica it should be fairly easy to grasp some of the concepts of the language.

The assignments are not difficult, though it requires the student to lookup for information in R forums, or stackoverflow.

Finally, Roger is a great instructor in my opinion - he's very calm and explains some difficult aspects of the language in a clear way.

I must confess that this course is difficult for who is beginning programming with R, the assignments require a lot of work and they are very involved. Nevertheless, I´m extremely satisfied. The book and the lectures are very good and the quizes and exercises forces you to really understand what you are doing or you cannot pass...it is what I really wanted! Thank you Coursera and special thanks to the instructor for his great work!