If I'm going to pay for a class, I'd like to actually learn something. This class was a complete waste of my time. I learned how to use swirl and that's it.

It is a course for professionals who are looking for a certification. Begginers who want to learn R at any level, should go somewhere else.

I understand the very basics of R and reading R code after this course. Writing useful code longer than a few lines, not so much.

The assignments can't be done without looking things up on your own. The course does not teach you how to do the assignments.

lectures are not in line with learning objectives

lectures are too short / missing real life examples

course needs a refresh

One of the worst courses I've taken. No practical application and transcripts that look like they were written by a machine.

实在是大大低于我的期望，教学内容和作业完全脱节，使得学生花费了大量时间自己没有头绪的学习，课程本省较为枯燥乏味，缺少实际操作性的演示，大部分是概念性和理解性的知识点，实际操作价值不大。

The week 2 assignment made me switch to another course.

want to unenroll!"""""""!!!! JIORU(£R*_)£(£

poorly designed

Thanks to Coursera and Prof. Roger D. Peng for offering such a wonderful course on R Programming.

Before the start of this session, my knowledge of R Programming is NIL. After attending the session, I'm confident that I could program in R and level of my knowledge is more than that of fresher. Thanks for the well designed course on R.

The Quizzes and Assignments are good and helped me test my understanding. These helped me improve my confidence level as well. I appreciate Professors special video session before difficult assignment. Just following these sessions closely, I could complete the assignment to my satisfaction and have confidence to attempt and complete.

I completed this course in the old format. Do I need to repeat it in the new format ?

The Discussion Forums are amazingly helpful in sharing subject knowledge and making the learning Fun. Getting help from some corner of the world and getting thanks from some other corner of the world makes this learning truly Universal and great Fun.

Thanks again to Coursera and Prof. Roger D. Peng.

Wishing Coursera and my Professors all the best and Success always.

Best Wishes,

S. Ramalakshmanan

1.The assignment is sophisticated but worth it. I agree with most people that the coding assignments are difficult and I usually spend at least one hour on each function. However, I think this is what makes the course worth it. The videos and swirl sessions are so basic that it only serves as a basic introduction and is barely useful for actual data processing and analysis. The assignments will force you to think about the steps need for building a function to serve your specific purposes.

2. Subsetting is the key and needs to be reviewed over and over again. Personally, I find subsetting in R powerful and a little bit confusing at the beginning. It is really the key to any manipulation of the data sets. Practive makes perfect. I think I will still spend time on reviewing them after the course.

This is an outstanding course. As an undergraduate student in the final year of my degree program, where not a lot of programming was covered, this course has really boosted my confidence in using R studio and has genuinely made me believe that I can programme anything I put my mind to. This course has also shown me that with a bit of practice each day, significant progress can be made to a level beyond what one may have imagined. This course has also enhanced my critical thinking skills, as programming needs careful logical thinking. At times, it can be so frustrating when a code is near functional but not quite working the way one intends, and so by persevering and sticking at it you will get there! I am now feeling ready to delve into the scientific world feeling that anything is achievable.

Challenging course that forces you to show what you got at the intermediate level in mathematics, statistics and computer science. Even that the SWIRL exercises were optional, it provided the underlying knowledge while the assignments (especially assignment 2 and 4) force you to organize your R-functions to solve the problems. The videos with Prof. Peng at JHU to install R studio, download and configurate the computer software were the easiest part meanwhile reading .CSV-files into R and writing the R-functions were the challenging part. Recommending the course to students who have studied computer science for a while and are bored on lectures with the regular stuff about IF-statements, looping and WHILE-statements. Regards from Sweden

I underestimate the lecture and it hit me back right in the face! The lesson is really good, and the assignment is really challenging. Not only we need to learn about R programming, but also some familiarity with git and github as version control method. The mentor respond is swift, additional lecture note from github is also really helpful. But it seems that sometime it will be really helpful if Coursera can facilitate to handle limited live session during lesson period so students can ask and get direct respond from lecturer, and might save hours of searching and experimenting if we can get a good directions at the time in need. Overall, excited to continue learning, thanks Coursera and ITB :D

This is course was pretty hard for someone like me without any background in computer programming. I had to take it twice to pass it. Luckily, there are many wonderful people in Coursera and in R who are always willing to lend a hand. Even if you pass all the basic requirements of the course i encourage you to do an exploration on your own. There are so many things to learn to make your job easy and to give inspiration to improve your performance in whatever field your in. It might feel like you're not learning at times or it's too difficult to continue, but once you get there, you'll realize how this wonderful new tool can help you with data analysis and presentation.

If there's one thing about this course that beats all the other regular ways to learn basic R (e.g. datacamp, swirl, reading a textbook, udemy, etc.) it is the MCQ exercises and peer-graded assignments. I can't begin to describe how satisfying it is to have to figure out on your own just 5 cleverly written MCQs for hours and then have the answer in the console finally match one of the choices.

Yes, there are other ways of learning R, but I find this one just sticks in my mind and gamifies the whole learning process. This could just be the strength of Coursera's system, I don't know, I haven't done enough courses to tell. But tell you what, I love this course.

Great class. Lecture was very to the point. I was a bit hesitant on taking this class given my limited programming experience and other reviewer's comments that the homework was significantly harder than the homework. Now that i have completed the class, I mind that as long as I listened to the lectures and did the practice questions, I had no issues completing the homework assignments (granted, occasional google & stackoverflow consult was needed just like any other programming class). I find the course material easy to understand and perfect for a data newb or someone who wants an introduction to data science and processing. Highly recommend this class.

Taking a course in R is an exciting journey into the world of data analysis and visualization. R's versatility and open-source nature make it a powerful tool for anyone interested in data science. Learning R allows you to harness the potential of statistical modeling, data manipulation, and data visualization, enhancing your analytical skills. Moreover, the R community is vast and supportive, offering a wealth of resources and assistance. As you progress through the course, you'll gain confidence in your ability to tackle real-world data challenges, making you a valuable asset in the data-driven job market. Dive into R; it's a path to success!

This was a challenging course. I have some experience in stats, but no experience with programming so I spent an extraordinary amount of time fumbling through the assignments. However, the effort was worth it. I am far from fluent in R, but I do feel like I know how to talk in R, pose questions about code, and begin to build functions with my knowledge. Have plenty more to learn, but fumbling through this course has definitely given me a good foundation. Tips for anyone thinking of taking the course: read the discussion forums, learn to look for answers online, and be patient if you're unfamiliar with programming languages.

I am a programming beginner and this class took me many many hours to work through seemingly simple assignments. When I did arrive at the right answer, I was happy and proud and recognized my growth. I guess that's the nature of programming. I found that the swirl practice assignments were helpful, if not simply enjoyable. In the forums there were a select few mentors that were quite helpful. I did almost prefer the robotic voice of the Data Science Toolbox over the videos that were presented here. I would have not been able to do the final assignment without dplyr knowledge from Getting and Cleaning Data. Continuing on!

I rate this course as the beta-testing (not that I had completed this course prior the beta started).

1) the course is still very good with a lot of explanations and examples

2) I liked the part about debugging because we don't see often this topic when learning a new language.

3) I liked (but it's only a cosmetic thing) that all the slides have the same template/organization ; it's easier later when we looked back at the lessons to find what we search.

4) one (very) minor comment : I watched the videos with subtitles (english) and sometimes it also writes when the instructor thinks "loud", or repeat a word several times

This course was a great foundational tool to get me started with R. Though the assignments were somewhat disconnected from the weekly learning, I enjoyed being able to think through problems and figure out how to solve them. I also enjoyed going to the forums after completing assignments to find out interesting ways that others had solved the assignments. I gained a lot of insight on various strategies and ways of thinking by being able to explore other's questions/comments/code snippets. I expect to take the next course after completing one on linear algebra first. Thank you so much for providing this resource!

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.