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Learner Reviews & Feedback for R Programming by Johns Hopkins University

4.5
stars
22,171 ratings

About the Course

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples....

Top reviews

EJ

Jul 11, 2016

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!

MR

May 11, 2020

Really interesting course. The interactive coding sessions with swirl are especially useful. Would be great, if you provided sample solutions for the programming assignments, in particular for week 4.

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3876 - 3900 of 4,720 Reviews for R Programming

By Tessa W

Feb 1, 2016

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.

By Bruno

Feb 29, 2016

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.

By Jose R

Oct 21, 2020

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

By Steve B

Jun 12, 2018

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.

By Polina B

Feb 16, 2020

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.

By Debayan D

Jul 17, 2017

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.

By Justin R

Jan 6, 2017

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.

By Ximena R

Apr 21, 2020

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.

By Fernanda K O

May 21, 2020

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.

By Dan H

Dec 18, 2017

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.

By Alister A D

Jul 4, 2020

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.

By Sem O

Jun 3, 2016

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.

By Alexandria T

Jul 31, 2021

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

By Vasileios P

Aug 18, 2019

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!!

By Rodolfo D M

Nov 19, 2018

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.

By Alessandro V

Oct 22, 2016

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.

By Jackie P

May 20, 2018

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.

By JONATHAN R W I

Feb 24, 2021

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.

By Sunjay M

Feb 29, 2016

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.

By Paris H

Sep 12, 2016

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.

By Robert L

Jan 25, 2018

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.

By Goziem M

Aug 28, 2018

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.

By SHASHANK D M I - D A

Jun 19, 2020

The course content is fairly good but the learning curve for the given assignments is very very steep especially the Week-3 and Week-4 programming assignment. I couldn't complete the assignments by the knowledge gained the video classes, and to depend heavily on the internet. I think the course makers need to re-evaluate the assignment's difficultly, as for a beginner who is just starting out in R Programming the assignment are pretty difficult.

By Deleted A

Jul 20, 2019

I seemed to have technical issues with for loops. certain things would work on a friend's computer, but wouldn't run on mine. The tools explained in the weekly lectures seem completely unrelated to the weekly programming assignments. I lost a LOT of time with the week 2 assignment because of the lack of guidance. I would have been completely hopeless if I hadn't found the reading section that actually taught the skills needed for the assignment.

By Nino G

Jul 24, 2020

Well, this course was very informative and forced me to delve deeper in R programming; However, If I were to recommend this course to someone, I would think twice before doing so. There are few things that one should consider when taking this course:

a) Lecturer speaks very fast and sometimes it is very difficult (or even impossible) to follow; b) material provided and explained during the lectures does not coincide with actual assignments.