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.

Assignments and swirl package were useful, but lectures were unengaging to new learners because material was taught in a very abstract way. Real, concrete examples in the lectures, maybe presented through an R programming interface (shared from instructor's screen) may have been more helpful.

Also, issues on programming assignment frequently pop up that were not covered well in lecture. For example, assignment 3 had issues with entries in the csv all being factors, so we often had to convert those to a more useful format. I didn't feel the lectures prepared me well for that challenge.

To start with the positive, the swirl exercises on the R console were very good. By far the most helpful thing about this course, and probably worth enrolling to have access on its own. Five stars

Biggest complaint: the programming assignments were significantly too advanced for the first level of this course catalog. Their lack of instructions also make it impossible to complete without some type of external guidance. Thankfully, the message board assists with some - but far from all - of these issues. One star

Videos were average, some more difficult to follow along with. Three stars

It was a decent introduction to R programming IF you already have some programming experience. I would never recommend this as a first programming experience to a novice programmer. That would be like throwing someone who has never swam in the Atlantic without a life boat! That said, if you have some programming knowledge to begin with, the Week 2 and Week 4 programming assignments were good. Week 3 was disjointed; it had NOTHING to do with the lectures from that week. I found the Week 3 programming assignment to be tor easy and, frankly, not very valuable as a learning tool.

I wanted to love this course so bad but unfortunately I couldn't. There was a great distance from what was taught in the lectures and what was asked for you to do in the assignments... and It's not a matter of knowing how to program. I know Ruby and Python but R is a very peculiar language itself. Perhaps they should invest more on gradual exercises like the one they advised to do on github or some easy statistical exercises... Now I don't know if I should take the next module or if I should look for something out of here where I can learn R. I see potential on this course.

As a scientific researcher, I find R programming a very useful tool. Therefore, I was excited when I found out about this course on Coursera.

Although I have learned a lot, I found the theoretical classes relatively hard to follow and the programming assignments really difficult to perform. I can understand this kind of method encourages the self-learning. However, I guess more theoretical support would be helpful, mainly for programming newbies. On the other hand, I really enjoy the swirl practice exercise and I really recommend them to future students.

Cheers, Jose

Being familiar with Python but not R, I didn't find this course too challenging. It is, however, rather topical and I would have liked to have spent a lot more time studying how data frames are organized and how to slice/subset them quickly - this really needs to be hammered into us as budding data scientists! Also, I felt that the lexical scoping assignment was contrived and frankly so complicated that I didn't really absorb what I was supposed to be learning. That being said, the last assignment was great!All in all I thought this was a decent intro to R.

I enjoyed watching video lectures and doing swirl exercises. They provide a good overall understanding of basic R commands and functions. The biggest weakness of this course is that weekly programming assignments are way beyond the level that you get from the videos and swirl exercises. Basically, you will need to figure out how to do them on your own through extensive googling. There is almost no guidance in the videos or other course materials. I am feeling like I wasted considerable time on those assignments because of that, hence I am giving 3 stars.

As a student of Computer Science and Engineering, I have done extensive coding. The course material is very easy to understand and is readily available in the book "R Programming for Data Science", written by the instructor himself, Robert D.Peng. However, I found the programming assignment for the 4th week quite challenging and took quite a bit of fumbling through the help manuals in R and using search engines. Students who are quite young in the art of programming will find the course assignments very difficult to understand and code the solution.

I understand that it must be a great challenge trying to teach R in four weeks. I feel the lectures were clear, the supplemental swirl assignments were beneficial, and that the discussion boards were fruitful. However, the assignments were ridiculous. Google is your friend with this course, as always, but if you're looking to gain a lot from this course, pay close attention to the lectures and the supplemental assignments in swirl. The assignments, in my opinion, were beyond the scope of the lectures and supplemental assignments.

There is a big disconnect between the lectures/learning material, and the actual programming assignments. Being new to programming, I found myself lost and lacking the "creative thinking" that seemed required to complete the assignments. The lectures taught a lot of new material, but there was no connection between weeks, and cumulative examples were lacking in order to teach newcomers how to tackle creating complex functions. Overall, I did learn, but I was left feeling disappointed once I encountered the final assignments.

The classes could and SHOULD be much better: deeper content, more references and material for reading. The video classes are really loosely tied together and aren't engaging. My perception is that I had video classes on one extremely superficial subject, while the assignments were different and considerably harder. I do not have a problem with hard and deep assignments, I quite enjoyed completing them, but I had higher expectations for the contents of the course itself. I do not believe it's worth investing in this course.

The video lectures and reading presented material well, and the programming assignments were reasonably well constructed, but there was a very limited relationship between those two elements of the course (the lectures/readings and the programming assignments). Because of this, according to the literature on teaching and learning, the course itself will have little to do with how well students retain and use the information. Perhaps the material here will be reinforced in later courses in the data science specialization.

The course videos and quizzes were really good. But the assignments are not even remotely approachable by the learner . The student can never complete the assignments with the things taught in the course. Only if we refer a lot of other materials and sample programs can we at least start to guess which functions to use in the assignment code . More sample programs are to be provided by the tutor so that the learner may become more familiar with the structure and usage of functions and other stuff in the code.

There is a high disparity between lecture content and the knowledge required to complete the assignments. It would be great to have a complete walk through of each assignment, showing the different ways in which the same functionality can be created, after having submitted an assignment. This would really had helped me to better understand why something is done in a certain way and improved my understanding of how R works. Currently there is zero feedback on completed assignments, which does not aid learning.

I like how this course really challenges one as slightly experienced in R. However, if it were me, I'll put this course as non-beginner level (I only survived since I have prior R experience) and actually put the pinned posts in forums in the actual course.

To anyone looking at reviews: If you're a complete beginner in R, and don't really plan to study R, it is advisable to not take this course until you have some prior experience. Unless you plan to put a lot of work and hours for this course alone

I had to search alot in order to complete this course. There isn't enough guidance for someone new. It would be very wise for a course review. It should have been more videos, analyzing real life examples and how a new learner should try to solve these problems. It was a real dissappointment for me. Swilr from the othee hand was an excellent tool which i really enjoyed . If swirl had somekind of explanantions of how you do something or what is the process for solving an iissue, it would be perfect!!

Existe um gigantesco abismo entre as palestras, os exercícios apresentados no “Assignments” e a codificação necessária para passar nas tarefas. Exemplo disso, é que não precisei de ferramentas para abordar as aulas e “Swirl” com o que me sinto confortável em usar.

Isto é um enorme prejuízo para os objetivos de aprendizagem do curso.

Em vários momentos, pensei em desistir por causa dessa consideração. Eu tenho experiência em codificação SAS, sou tradicionalmente um bom aluno, então isso é frustrante.

It is easy to follow, it should be a 2 week university course, but IMHO it should cover more about the data type problems that can arise with R loose data types. It is focusing too much on the code profile concept without leaving interesting knowledge about that. It should cover better the native idea/implementation about computation as single instruction multiple data, which is not well covered. In the end, this is one interesting aspect of the language that makes it useful for data science.

This course does a good job of presenting R concepts to users and I felt that the lectures, quizzes, and swirl assignments were all in line. However, when it came to the R Assignments, they required knowledge beyond that which had been taught in the course. I believe this is the intention, though not a gradual way for a beginner to learn R. Additionally, peer-grading is flawed in that fellow students who don't know the correct answer or couldn't finish their own code are grading everyone.

This course is well made and i learned a lot from it. However it is very far away from being the best it can be. There should be more swirl exercises, specifically about lexical scoping. The narration could be made better without the "ehh" stuff. The explanations could also be made clearer. Finally the assignment instructions are sometimes confusing. I believe it is ok to extend the word count if that means clearer and unambiguous instructions. A good course, but i can be a lot better.

It was a good class to begin with however it would have helped to tailor it more towards newcomers to programming language in general. I also would have like it if Roger would have highlighted or circled, or something to specify where in the slide he was talking about. I felt that at times it was hard to follow where exactly he was talking about and what part of the code/function he was mentioning. Im a visual learner and that would have been greatly beneficial.

Overall a good crash course and introduction to R. Its a lot to learn in 4 weeks and some of the assignments were challenging (which I liked). I think the course is worth taking but I do wish the material and assignments were packaged better - more aligned. Just be prepared to spend a lot of time online reading, researching, and learning some concepts on your own. Don't expect to learn everything from the lectures and materials to be successful in this course.

A difficult course to follow. If it where not for a random hidden forum post with an additional lecture for the programming assignment 2 I would have struggled to understand quite what the assignment wanted.

Programming assignment 3 was also difficult for a novice coder and I felt out of my depth when comparing teachings to assignment.

I think the course could do with more lectures and increase length to at least 2 weeks.

Good points, hell I learnt a lot.

This course would have learnt itself better to interactive-based learning. It took me a long time to build R scripts because a lot of what I needed to do was not covered in the lectures. Because of the wide experience range of students, the assignments should adhere to what is covered in class with an option for extra credit questions.

I will continue on the track, but will also pursue an interactive learning option to supplement what is taught here.