Not suitable for beginners.

I am a total beginner in R. As mentioned by many other learners, the projects from the course is beyond what we had learned from the videos (the videos are quite fundamental and are useful to beginners, except the lexical scoping part which I still do not understand even with the project assignment two), which is why I am giving three stars. However, it exposes us to the real working environment when you are given a project without any guides. We are required to think independently how should we tackle such kind of situation when we are facing programming problem. You may have the idea but you do not know how to code it. Then you go through forums, be it Coursera forum or StackOverflow. You will enjoy the hard time when you are stuck and when you do not understand the forum contents. But you will also enjoy the sweet time when you have finally figured out the codes that work! The course is recommended for those who like to accept the challenge.

I learned a lot of things in this course, but I can't say that I'm pleased with the course overall. First of all, I found really frustrating that there was no connection between assignments and each week theory with a huge difficulty leap between them. Secondly, videos was kind of useless as the tutor was just reading the slides, and thirdly there was no consistency between each week curriculum, it lacked coherence. Even so, I learned a lot of things, and after all this frustration I find myself more confident in using R language. In addition, the tutors are present in the discussion forum and they are really really helpful, answering questions and provide extra material for the assignments, which in my opinion should be integrated in the main course. If this course was a couple of weeks longer, and there was consistency between theory - assignments, I think that it would be much better.

In short, I learned a lot in this cocurse but I would not consider it for beginners with little programming experience. I spent at least 3-5 times more doing the assingtments. The information presented was very valuable but the pedagogical part was not well done. The chunks of information were poorly connected between themselves, making the learning process tidous and hard to achieve. The visuals were very sloppy with only white slides and a font too small. For these reason the lectures were boring and unappealing. My suggestion is to take more care of the didactic aspect of the course. Many times I had to watch YouTube videos on the same topic that I had just seen, and I can say that a colored diagram made all the difference between understanding everything and not understanding nothing at all.

There is an incredibly wide gap between the lectures and the exercises presented on Swirl and the coding needed to pass the assignments. So much so that I didn't have to tools to approach the assignments with what I feel comfortable using. This is a huge detriment to the learning objectives of the course.

At several points, I contemplated quitting because of this consideration. I imagine it is a huge hurdle. I have no coding experience, but I am traditionally a good student so this is frustrating. This is my first Coursera sequence, though I have taken online classes before through more traditional universities.

For this second course installment of the Data Science Specialisation, there is an immense gap between the lectures and the assignments. I completely understand not being "spoon fed", which is a critical aspect of learning anything on your own. However, the jump in expectations between Programming Assignment 2 and Assignment 3 was incomprehensible. You could work your way through #2 but with #3, it felt as though you had a plethora of information thrown at your way, adding to the confusion, which you then had to stare at for what felt like "light years" to fully decode, in order to get through the quiz.

Even though the video lectures, discussion forums, swirl & reading resources are informative, there is a huge disconnect between the assignments & what is taught. It is impractical for people who have just been introduced to R(with no background in programming) to take up this course.

The graded assignments should be made simpler or should be preceded by smaller ones which help first-timers get used to coding in R. I do not think Swirl; even though a valuable resource; achieves this task remotely.

The level of teaching does not match the level of the assignments. They teach you like you're just going to be quizzed on the vocab and some really simple functions, but then the programming assignments are WAY more complicated than anything they actually taught you. I get that in data science we are supposed to learn how to solve problems, but the instructors shouldn't be intentionally creating problems where we have to go and spend many hours teaching ourselves the material just so we can pass.

It was a little difficult grasping functions as I didn't have much programming background. The swirl practice modules were great but I wish they constructed some lessons that would build a function from top to bottom like we were asked to do in the programming assignments. The lectures, swirl practice modules, and quizzes were great but they all re-iterated the same basic information. I wanted to learn and practice building more functions by applying the basic information to do complex tasks.

The course is OK. This biggest frustration was that lectures were quite unhelpful for the programming assignments they give you. They are not engaging and get very technical very quickly. Be prepared to use extra resources/websites to help get better explanations. The swirl activities are optional for the grade, but a MUST for understanding material--do them. I found that I was able to complete most of the pieces of the course in less time than they tell you next to the descriptions.

1) This course is NOT for beginners in R programming. Huge gap between lectures and assignments. Swirl lessons are cool, but anyway they don't explain enough.

2) I understand that studying is not always a joy, but lectures of this course are boring. First, slides come with brief comments of instructor. And second, it seems like the instructor speaks with no preparation as there are a lot of stammers, tongue slips, "sort of", "kind of" etc. It annoys a lot...

I did learn a lot, but not from the course given and, unfortunately, not from the instructor. I have to google and read through many R docs and articles outside this course to complete the assignments. I know Google is my friend, but I am rating the course :D. The course is somewhat not well-structured. For someone who is really new to R, guidance is extremely important considering there are many paths can be taken to solve data analysis problems using R.

The course is too ambitious and some themes are explained in a very plain and boring way. I can't say you will learn nothing, the course isn't too bad, but if you have no prior experience with programming o even if you have but not in R, the course programming assignments will be a little difficult and the material. If you want to complete this course you will have to invest a lot of time searching for things and/or waiting for help in the forums. 5/10

I learned a lot from this course. My only concern is that, most of the assignments did not match with what was discussed in the lectures. It became difficult for beginners like myself to catch up. It seemed that the lectures were incomplete. I hope this gap between lectures and assignments will be addressed soon. Nevertheless, I learned a lot from this course and now I can say I know something about R programming. Thanks Coursera.

This course's lectures give a good introduction to R programming. However, good practical exercises are missing from the class. The assignments ask a lot of the students, but the lectures come no where near preparing one to complete one of the assignments. The programming skills talked about in lectures are super basic, and then the assingments are far, far more complex.

Ultimately, I did learn a number of skills. Be aware that the actual course materials (lectures and some very basic swirl exercises) do not prepare you adequately for the assignments. One of the mentors has created a repo of 12 exercises that are not a part of the course that are critical to learning the skills if you have no prior programming experience.

Difficult to follow and course curriculum not fully in line with the quiz. This course could easily span 6 weeks to avoid information overload and unnecessary time pressure while working full time and with family responsibilities. Optional SWIRL exercises should be revisited between Course 2 and Course 3 as there's very little time within each week.

I learned something, of course, in this course. But without previous experience in data science, I found it OK to understand the lectures, but always got lost in the coding assignments. I tried to finish it on my own, but it turns out I have to search everything online. I felt that there's a big gap between lectures and assignments.

For me as non programmer, the course resulted sometime hard to follow. Simply adding a pointer when Prof. Peng is showing a slide it would improve the understanding.

While the lectures were informative, the programming assignments went way beyond what was covered in the lectures.

This course was not what I've expected. The functions lessons were not achieved, because it was not teached well.

Presenter uses undefined/unexplained terms regularly which most users would not be familiar with.

very good course but you need much more time then announced to finish the assignments

Tutorials are indispensible for students to complete the assignments.

This course is for programmers.