Excellent course! I already knew a lot about R - but this class helped me solidify what I already knew, taught me lots of new tricks, and now I have a certificate that says I know `something' about R!
Very challenging, but good course. I've been programming in R for over a year, but there were still some things for me to pick up in this class. Assignments were a challenge, but satisfying to tackle.
por Juergen K•
Not very well organized overall. The assignments were fun, but I had to do extensive research online to find out how to answer the questions being asked, which made me wonder why I had sat through the videos. Sometimes I didn't even use what I learned in the videos to complete that week's assignments. The videos are far too theoretical, they probably would have been useful for someone familiar with R or S, but for a new user they required a lot of rewinding and without practical examples it was hard to actually remember what was being taught. In the rare instance practical examples were given the material stuck much better!
por Gabriela Á L•
The assignments are not gradual, I mean the content of the classes is not enough for the completion of the assignments. I think I would have appreciated more content in the classes, more explained exercises so that the making of the assignments wouldn't have been so miserable! It's a very hard course.
But I've learned a lot on my own, thanks!
por Diego V•
Huge disconnect between the canned lectures (almost all not by Peng) and the exercises. Moreover, other than generating random number distributions, there are no examples of the lecture material worth anything. Given the subjects covered, the course could be great
por Javier C•
The contents of the lectures are quite hard to follow, and exercises do not have much relationship with them. Difficult to follow the course, even with other programming languages skills.
por Biel G P•
The assignments are too difficult compared with the knowlegde taught in the videos and swirl
por Li C W•
I am extremely disappointed with the quality of this course. I am a professional analyst and have some years of programming, I intended to "formalize" my knowledge in R and data science by taking this course. This course is organized in a very poor manner, lectures and assignments are completely disconnected, the instruction in the assignment is also extremely poor, it is very hard to understand what the learner is expected to do, it is very frustrating and I cannot imagine this course is intended for "beginner". I managed to finish that just because it is sponsored by my company. 0 out of 5 stars
por Madhubalini V•
the instructor is like this is ABCD.., and the assignment is like write a report on a topic. the course is too hard for a beginner, then the instructions are confusing.
por wang z•
por Ramalakshmanan S P•
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.
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.
por Emre Y•
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.
por Oka M S•
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
por Edmund J L O•
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.
por Wei D•
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.
por Tomohiko J M•
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.
por Garrett F•
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!
por Jonathan B•
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
por Paul L•
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.
por George G•
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.
por Alvin C Y H•
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.
por VADALI S G•
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.
por Anand K•
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!
por Marcelo S•
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.