I'm not going to finish this course due to a number of reasons, some of them being my personal gripes, some being very fatal flaws in the course itself. The first gripe is that there is an obvious lack of any kind of script during the video instruction. I can't tell you how many times I was distracted by the professor just simply not being able to speak a clear sentence without stuttering at least twice and saying "um" or "uh" no less than 10 times at points during single sentences. I am obviously not sure if he has a stuttering problem, which is why I tried my hardest to just deal with it, however, after realizing that what he's saying in the videos isn't matching what's being lined out in the written lesson I knew that it didn't matter if he stuttered or not, he's just simply not teaching the same things that are being asked on the quiz. I don't know where this reading is supposed to be. I went all out and bought the associated book, and it's literally an enterely different lesson arc than what the videos line out. In the documentation? That's where I'm pointed to most of the time but I hate to tell you that if someone could learn how R syntax worked just from the documentation there wouldn't be courses for it. So, the course goes from a shaky understanding of what 1/4 of the base functions are in R, to writing your own functions and expecting you to understand and remember the syntax for all those other functions you just learned or didn't in some cases, you just have to look up how that works and make it happen. There is no guidance other than, here's half the answer, good luck with the rest. The other part of the course that I just absolutely can't stand is the exercise model SWIRL they came up with to test code. At least three times I had the correct answer, but the spaces weren't the same so it didn't register as correct, and I spent over an hour on three questions trying to understand why I was wrong when I wasn't. That, right there, is the biggest reason I'm not going to even attempt to complete this course and am moving on to something else that will hold my hand a little more with the syntax that I'm just now learning, rather than expect me to understand it after just a week. I hope that anyone else attempting this course has a better time with it. The professor is obviously knowledgable with the language, I'm just not sure if he's a good relay for that information, at least for me he wasn't.

The best part of the course is the swrl exercise. I really don't like the other aspects: 1) the video format of the classes, where 1a) the speaker improvisizes and then continuously corrects what he says, making it very difficult to understand the new concepts. 1b) Also, one potential advantage of the video format could be to observe things while are done on the screen... on the contrary, we generally can see only slides where everything has been already typed (making very hard to understand at what part of the script the speaker is referring to each time... maybe using a pointer would be better, so that he can direct our attention at the parts of the scripts he is commenting...1c) Also, the very few times we are showed a real screen, the quality of the video is so poor that it is impossible to understand anything. 2) the material offered are very poor. After watching these poor quality video, a text reference would be incredibly necessary. On the contrary, we are almost always only given a transcript of the video, which means that we have no clean text we can refer to. I really don't like the lack of formality of this course. 3) Additionally, the slides that we watch on the video, most of the times are not downloadable. 4) And never ever the script showed in the video are made available, 5) having the exercise reviewed only by peers is conflictive, people will tend to give the highest mark just to be friendly or out of fear in case a revengeful student will give a low mark in the next assignment just because we marked their assignment honestly...

I had indeed to look for codecamp to practice all the small commands how to deal with vectors. Swirl does not allow you to follow up so clearly. I wish you guys could implement a little R interface so we can follow you closer.

The last project quiz demands you a huge amount of time, if you do not have much experience. They could shorten a little the questions. I know that one takes to the other, but I only had time to finish the first and understand. Yes, perhaps I am not the best, but you are offering the course to people who are not born programmers.

I think that it would benefit strongly from a clear distinction between how to deal with vectors, matrix, data.frame, etc. separately instead of the huge videos with bullet points of the potentialities. We need to practice more, I like theory and I know how important, but I dont think that I learn much from the lessons or quizzes how to code something like the last part. I dont think it build my knowledge until I understand how to create that script for week4. I had to look around in all the internet, buying books. Read more. Just my opinion. I think you guys could give small scripts or asking smaller tasks to lead people until they understand how to build that.

Also has its positives, I really learnt great tips and technically I know a lot of R potential.

Some of the material was not useful in completing the assignments. Profiling was not useful in this regard. While it is useful in the real world, it was unrelated to the assignments. Also, Better examples of functions like lapply, tapply etc. besides using random data would be more likely to make sense what the function is doing. Also, there are references to statistics/statistical methods that the student may have no background in. This is also not helpful for explaining the material. The video content is largely just reading the text of the slides. It takes much more time to watch the reading of the slides than just to read them. This is not the best use of video. Neither is watching the instructor sitting in his office talking. It would be better to see a concrete problem solved, and explain why the steps taken are used. The problem could be related to the assignments but different enough to not be copied. I had to rely heavily on online resources and help files to get answers to things I think should have been part of the course material, as this is an introductory class.

I wish to have two comments:

First, I think it would be wonderful if in addition to the certificate, Johns Hopkins could also provide the course taker a kind of transcript or just the total grade.

Second, although I managed to earn 100 points for all the graded assignments in this course, I really hate the way the Programming Assignments were designed - they had too little to do with, and go too far beyond, the knowledge and skills presented in all of Professor Peng's lectures. As a university professor with over 23 years of teaching experience, pedagogically , I find this very unfortunate/bad. I've been simultaneously taking a course in Duke's Statistics with R specialization, and I find that Duke's course does much better - there is a great match between their detailed lectures and their assignments, and the assignments have very detailed guidance, too. I do not know whether I should go on and take the next courses in this Johns Hopkins specialization or not. I feel quite deterred and unhappy, even though I strongly wish to study R for data science.

I feel like the description for this course needs to be a lot more explicit about the difficulty level. It is marketed as a course for beginners of which I am one. I had no previous programming experience and the assignments in this course were probably the most difficult assignments I have ever done. It was only possible for me to complete with a lot of self-directed learning through internet searches, and a lot of help from my brother who is a programmer but hasn't worked with R before. The difficulty level of the assignments was quite frustrating because there was a huge gap between the things we were taught during the course of the lectures each week and what we were then asked to do in the programming assignments. Overall I am glad I completed this course, but I cannot stress enough that it was very, very difficult and beginners without the same resources that I had (i.e. programmer brother) may find it impossible.

The course may be rather hard for someone without earlier basic experience in R or in programming. It's not bad, though some aspects could be discussed more in depth. The whole course refers only to basic functions of R, it does not teach tidyverse package, which is much easier to grasp for beginners.

Anyway I'm glad that I took this course, as now I understand why tidyverse (especially piping, filter, arranging) is more intuitive than original R functions.

The assignments could be written more in context of what is taught in the course, they either introduce some new concepts (which should not take place at the stage of testing) or do not test some important aspects of the course (debugging, profiling).

Prof. Peng is true expert in R. If you listen to him carefully and occasionally use other resources, as he suggests, you'll succeed. But do not expect prof. Peng to explain you everything in "for dummies" way.

So the course is a mixed bag.

PROS: The lecture content is useful, albeit a bit dry. I can't give them too much slack for the dryness, after all it's coding. However, they could have shown more real-time coding, rather than just scrolled through powerpoints with the Command Window pasted. You definitely need to have R open when following along with the lectures. The quizzes are also quite useful, as you're required to know both the background of how things work and use the commands learned from the lecture.

CONS: The assignments assume you know a lot more than the basic knowledge, and there's no real way to know how to do the assignments just from the lectures. The quizzes tend to be on the easy side and the assignments ramp things up quite quickly. There's no intermediate material to test your skill. You have to have worked in R to have even a minor chance at succeeding on the assignments.

Well the material is really good but i don't like the fact that since its supposed to be for beginners that we have to use stuff we really didn't see or explained in detail at the lectures so as a result i have to search long hours in the web.I understand seeking information is part of the course but spending so many hours trying to figure out things is not really the ideal,since people who choose distance learning are most times occupied with other duties and try to squeeze the courses into their schedule.I also think the amount of information especially on the first week that i just finished is too much for just one week and for someone new to the subject.

I am currently taking another coursera class 'Python for beginners' which i can say is very comprehensive , step by step and is intended to beginners. Also, there is great support from the instructor in the forum.

Week 2 and 4 programming assignments were an excellent intro to R syntax.

Week 3's "lexical scoping" programming assignment had ZERO value - the concepts were confusing and completely un-necessary for a beginner. The provided code was unreadable. A "mentor" posted an explanation of how that assignment worked on the course forum - it took a monument to programming pedantry to explain how the code worked.

To anyone else planning on taking the course: Take Weeks 2 and 4 seriously. Don't worry about Week 3 - just copy & paste someone else's answer to get through it. (That's right, I advocate CHEATING to get through this.)

The pointlessness of Week 3's assignment is the only reason why I rate this course a "3 star". If the Week 3 assignment is replaced with something more productive, I would gladly change the rating to 5 stars.

The course is a good introduction to R programming. I learned a lot from it, however, it was very very frustrating at times. The quizzes and assignments have very little to do with the videos or textbook. There is very little guidance overall. The two assignments that I was the most able to benefit from have videos on YouTube with a step by step description of how they should be solved. I tried to solve the assignments first, then I watched the videos and was able to understand why my functions were not working, so I went back and edited them and they worked! I think videos going over the assignments or quizzes - that could maybe be made public after you try to submit at least something - would be of huge help. As it is, the course doesn't prepare for the assignments and there is no guidance while doing them.

the videos are super boring and i think the should come with the text option like the data scientist toolbox.

also the hesitation when the teacher talks is a huge problem, the bot doesnt have that issue and tbh its a bit clearer to understand.

IMPORTANT: the depth of the lectures is quite poor vs the assignments, and as I understand that the use of documentation and help forums is paramount, I consider that the lectures should at least mention ALL of the functions with which it is expected to carry out the projects. for the second programing assignment even though I was able to use the example in the instructions to carry out my solution, I have to say I just don[t understand the reason why 80% of the code lines should be there. that sort of lecture or instruction is clearly missing.

I think giving this course a three is generous considering how incomplete it feels at times. There is a giant gap between what you learn in the lecture videos and what you are expected to do on the quizzes and assignments. The professors also don't really know how to help students as it seems they are too detached from looking at this course from the perspective of a student who has to learn a complex language. Some of the discussion boards are very out of date and give the wrong information about what you have to do or how to install some of the features that you need (besides Rstudio & R). I have worked with R before taking this course and it was still very frustrating. You do learn a lot of material, but not everything is explained well enough to fully understand the material.

although it gives an introduction to R, however the structure of the course overall was not up to expectation or objectives of it.

the videos were very much theoretical and boring. Introducing too many concepts (although basic) was not related to the programming assignments. I had to google almost all assignments. It's arguable that this is one way of learning and more of realistic. But on the contrary, as I'm paying to get the knowledge I shouldn't be wandering around to understand something that should've been taught in the lectures.

Moreover, I think that the videos need to be updated, the mentors need to be more involved in the forums, and the way the slides are presented within the videos should be more interactive or dynamic rather than being just captured lines of codes.

The lectures give the bare minimum of information needed to complete the actual assignments. There is absolutely no way to complete this course and the assignments without prior experience in programming or R itself. The code needed to complete the assignments is not explained in the lectures, and if it is, the lectures give little to no guidance on how to manipulate the information to get your desired results. Online communities are a godsend in completing this material. I understand that learning to code in R is an independent process, mainly one of trial and error, but without the proper foundation (which is barely provided here), one finds themselves agonizing and floundering completely in a sea of information that mist be deciphered on your own.

This course is not for the faint of heart. The course materials only give you the fundamental concepts but the assignments are extremely challenging. If you have no previous experience in R or computer programming then be prepared to spend hours researching online and experimenting with different techniques in order to get the assignments done. Also, the assignments are very time consuming, so I would advise that you complete the lectures as early as possible so that you can spend most of the week working on the assignments.

Nevertheless, now that I have reached the end of this course, I must say that I learnt a lot about R over the 4 week period. If you are up for the challenge I would recommend it.

Dr. Peng and colleagues communicate well and provide a reasonable overview of the R platform. I took this class hoping to take my reasonable prowess in Stata and bring it to R. The biggest gripe I have is that the course stuck almost entirely to how to program in R rather than how to perform statistics in R. Given that the historical purpose of R as described in the course was to start using it for statistics and then learn additional programming as you go, this approach to the course seemed a little backwards. I have a reasonable working understanding of R as a programming language but now I am on the lookout for a course that can let me apply my statistical knowledge to working in R.

Swirl lectures were very innovative and helped me significantly to grasp the topic. They can perhaps be updated to get into more examples/complexity- especially *apply functions and base graphics.

The lectures were dry and difficult to understand. The instructor though experienced was adding only a little bit more to slide content. Often I was able to read the slides but instructor was still reading off that.

It would have been great to point out that more practice will be required to gain significant expertise in R and any direction to get more practice.

Overall satisfied and appreciate the efforts taken to set up this course. Only made these suggestions to improve course.

In general, the course enabled me to understand the semantic and syntax and be able to process data with it, using basic functions.

I also want to highlight that I really liked "swirl" and it is a great tool to get into the subject!

Where I would encourage you to do better are:

* the slides of the ppts are in low resolution and the fonts are two small in my opionen (there are also no colours)

* Dr. Roger D. Peng did not speak that clearly and often he go muddled.

* The assignment in week 3 is pourly explained and only some further explanation in the forum could clearify the major aspects. Also it was quite unclear for me, how it is related to the learning content of week 3.

Course lectures do not adequately prepare students for the exercises. Lectures were very basic and the programming assignments required a lot of learning beyond the lectures. By supplementing with info from other online searches i was able to learn enough to complete the assignments. I feel like I learned a lot this way-- however-- i really didn't need the course to do this. I don't feel that the course lectures added anything that i couldn't have found on the internet.

Also-- if you can't stand the sound of people swallowing and slurping when they talk-- you might want to avoid these lectures-- I couldn't stand the slurping noises this guy made when he talked!

Dr. Peng is great at teaching, and the lectures are not hard to follow. The recommended e-book is almost a transcript of the lectures' examples, and I really recommend getting it (I got it on print, as I like to make annotations while following the videos).

That being said, the Programming Assignments are extremely difficult for anyone with no programming background. The Assignments do not require just what is being taught, and demands a lot of google and stack overflow research in order to solve the problems. If you are doing other Coursera courses and/or working at the same time, I recommend you invest time in this and do not let the assignments for the weekends.

I really struggled - coming from a zero programming background. I recommend tons of reading, practical exercises, swirl is a bit of a savior and so is stackoverflow. Even with all of that, I struggled to get my mind to think like a programmer and structure the thoughts into plans for the assignments and tests. I think there needs to be a course before this that teaches one what the first step of solving a programming-related problem; eg one that focuses on flow charts, breaking down the question, etc... It literally is like learning a new language : you need to keep reading and practicing and watching/listening to others do it until you start to get it.

This is a very challenging course. The slide-based quizzes and programming assignment up till the third week are fairly easy, however, for an intermediate level course, the programming assignment on week 4 is very tough. I found much of this course more as 'R as a programming language' than as 'R for statistics and data analysis'; the latter was what I was looking for. On the positive side, the course gets into the nuts and bolts of R and gives an overview of many different aspects of R as a programming tool. All in all, I found many new things to pick up from the video lessons and programming assignments, but there are equally many rooms for improvements.

This course was mostly self learning. It gave me a framework to go along but what is presented in lecture and assignments are completely different. The discussion board and mentors are really good resources and can provide pointers to move along. It is definitely not a class that can provide sufficient information to learn and build applications, but the individual's effort in passing the quizzes and the projects will. It is up to the student to figure out through stack overflow, youtube, and other search result to figure out how to complete these assignments. I believe the assignments given from this class are realistic to real-world situations.

Overall, a somewhat challenging course due to the complexity of assignments not matching the lectures. The lectures were simplistic, which would be acceptable for this course level, but applying this information to the assignments went well beyond what the instruction given. I would not expect the assignments to be a recitation based on the lectures and expect their difficulty to increase. However, I spent a considerable amount of self-learning to complete the assignments. I would have spent more time, if it weren't for a couple of contributors/mentors on the discussion forums helping us along.