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Rプログラミング に戻る

ジョンズ・ホプキンズ大学(Johns Hopkins University) による Rプログラミング の受講者のレビューおよびフィードバック



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....



Jul 12, 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!


Aug 12, 2019

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.


Rプログラミング: 3176 - 3200 / 3,862 レビュー

by Joana P

Nov 20, 2016

I had indeed to look for codecamp to practice all the small commands how to deal with vectors. Swirl does not allow you to follow up so clearly. I wish you guys could implement a little R interface so we can follow you closer.

The last project quiz demands you a huge amount of time, if you do not have much experience. They could shorten a little the questions. I know that one takes to the other, but I only had time to finish the first and understand. Yes, perhaps I am not the best, but you are offering the course to people who are not born programmers.

I think that it would benefit strongly from a clear distinction between how to deal with vectors, matrix, data.frame, etc. separately instead of the huge videos with bullet points of the potentialities. We need to practice more, I like theory and I know how important, but I dont think that I learn much from the lessons or quizzes how to code something like the last part. I dont think it build my knowledge until I understand how to create that script for week4. I had to look around in all the internet, buying books. Read more. Just my opinion. I think you guys could give small scripts or asking smaller tasks to lead people until they understand how to build that.

Also has its positives, I really learnt great tips and technically I know a lot of R potential.

by Andy T

Nov 04, 2016

Some of the material was not useful in completing the assignments. Profiling was not useful in this regard. While it is useful in the real world, it was unrelated to the assignments. Also, Better examples of functions like lapply, tapply etc. besides using random data would be more likely to make sense what the function is doing. Also, there are references to statistics/statistical methods that the student may have no background in. This is also not helpful for explaining the material. The video content is largely just reading the text of the slides. It takes much more time to watch the reading of the slides than just to read them. This is not the best use of video. Neither is watching the instructor sitting in his office talking. It would be better to see a concrete problem solved, and explain why the steps taken are used. The problem could be related to the assignments but different enough to not be copied. I had to rely heavily on online resources and help files to get answers to things I think should have been part of the course material, as this is an introductory class.

by Tomasz J

Nov 15, 2017

The course may be rather hard for someone without earlier basic experience in R or in programming. It's not bad, though some aspects could be discussed more in depth. The whole course refers only to basic functions of R, it does not teach tidyverse package, which is much easier to grasp for beginners.

Anyway I'm glad that I took this course, as now I understand why tidyverse (especially piping, filter, arranging) is more intuitive than original R functions.

The assignments could be written more in context of what is taught in the course, they either introduce some new concepts (which should not take place at the stage of testing) or do not test some important aspects of the course (debugging, profiling).

Prof. Peng is true expert in R. If you listen to him carefully and occasionally use other resources, as he suggests, you'll succeed. But do not expect prof. Peng to explain you everything in "for dummies" way.

by Daniel F

Sep 03, 2016

So the course is a mixed bag.

PROS: The lecture content is useful, albeit a bit dry. I can't give them too much slack for the dryness, after all it's coding. However, they could have shown more real-time coding, rather than just scrolled through powerpoints with the Command Window pasted. You definitely need to have R open when following along with the lectures. The quizzes are also quite useful, as you're required to know both the background of how things work and use the commands learned from the lecture.

CONS: The assignments assume you know a lot more than the basic knowledge, and there's no real way to know how to do the assignments just from the lectures. The quizzes tend to be on the easy side and the assignments ramp things up quite quickly. There's no intermediate material to test your skill. You have to have worked in R to have even a minor chance at succeeding on the assignments.

by Maria K

Apr 04, 2018

Well the material is really good but i don't like the fact that since its supposed to be for beginners that we have to use stuff we really didn't see or explained in detail at the lectures so as a result i have to search long hours in the web.I understand seeking information is part of the course but spending so many hours trying to figure out things is not really the ideal,since people who choose distance learning are most times occupied with other duties and try to squeeze the courses into their schedule.I also think the amount of information especially on the first week that i just finished is too much for just one week and for someone new to the subject.

I am currently taking another coursera class 'Python for beginners' which i can say is very comprehensive , step by step and is intended to beginners. Also, there is great support from the instructor in the forum.

by Michael Y

May 11, 2018

Week 2 and 4 programming assignments were an excellent intro to R syntax.

Week 3's "lexical scoping" programming assignment had ZERO value - the concepts were confusing and completely un-necessary for a beginner. The provided code was unreadable. A "mentor" posted an explanation of how that assignment worked on the course forum - it took a monument to programming pedantry to explain how the code worked.

To anyone else planning on taking the course: Take Weeks 2 and 4 seriously. Don't worry about Week 3 - just copy & paste someone else's answer to get through it. (That's right, I advocate CHEATING to get through this.)

The pointlessness of Week 3's assignment is the only reason why I rate this course a "3 star". If the Week 3 assignment is replaced with something more productive, I would gladly change the rating to 5 stars.

by Lama A

Oct 02, 2019

The course is a good introduction to R programming. I learned a lot from it, however, it was very very frustrating at times. The quizzes and assignments have very little to do with the videos or textbook. There is very little guidance overall. The two assignments that I was the most able to benefit from have videos on YouTube with a step by step description of how they should be solved. I tried to solve the assignments first, then I watched the videos and was able to understand why my functions were not working, so I went back and edited them and they worked! I think videos going over the assignments or quizzes - that could maybe be made public after you try to submit at least something - would be of huge help. As it is, the course doesn't prepare for the assignments and there is no guidance while doing them.

by Ali E

Oct 18, 2016

although it gives an introduction to R, however the structure of the course overall was not up to expectation or objectives of it.

the videos were very much theoretical and boring. Introducing too many concepts (although basic) was not related to the programming assignments. I had to google almost all assignments. It's arguable that this is one way of learning and more of realistic. But on the contrary, as I'm paying to get the knowledge I shouldn't be wandering around to understand something that should've been taught in the lectures.

Moreover, I think that the videos need to be updated, the mentors need to be more involved in the forums, and the way the slides are presented within the videos should be more interactive or dynamic rather than being just captured lines of codes.

by Emily D

Jan 10, 2020

The lectures give the bare minimum of information needed to complete the actual assignments. There is absolutely no way to complete this course and the assignments without prior experience in programming or R itself. The code needed to complete the assignments is not explained in the lectures, and if it is, the lectures give little to no guidance on how to manipulate the information to get your desired results. Online communities are a godsend in completing this material. I understand that learning to code in R is an independent process, mainly one of trial and error, but without the proper foundation (which is barely provided here), one finds themselves agonizing and floundering completely in a sea of information that mist be deciphered on your own.

by Melissa M B

Jul 02, 2020

This course is not for the faint of heart. The course materials only give you the fundamental concepts but the assignments are extremely challenging. If you have no previous experience in R or computer programming then be prepared to spend hours researching online and experimenting with different techniques in order to get the assignments done. Also, the assignments are very time consuming, so I would advise that you complete the lectures as early as possible so that you can spend most of the week working on the assignments.

Nevertheless, now that I have reached the end of this course, I must say that I learnt a lot about R over the 4 week period. If you are up for the challenge I would recommend it.

by Ira L

Sep 16, 2017

Dr. Peng and colleagues communicate well and provide a reasonable overview of the R platform. I took this class hoping to take my reasonable prowess in Stata and bring it to R. The biggest gripe I have is that the course stuck almost entirely to how to program in R rather than how to perform statistics in R. Given that the historical purpose of R as described in the course was to start using it for statistics and then learn additional programming as you go, this approach to the course seemed a little backwards. I have a reasonable working understanding of R as a programming language but now I am on the lookout for a course that can let me apply my statistical knowledge to working in R.

by Sanil S

Dec 16, 2017

Swirl lectures were very innovative and helped me significantly to grasp the topic. They can perhaps be updated to get into more examples/complexity- especially *apply functions and base graphics.

The lectures were dry and difficult to understand. The instructor though experienced was adding only a little bit more to slide content. Often I was able to read the slides but instructor was still reading off that.

It would have been great to point out that more practice will be required to gain significant expertise in R and any direction to get more practice.

Overall satisfied and appreciate the efforts taken to set up this course. Only made these suggestions to improve course.

by Tobias H

Mar 21, 2019

In general, the course enabled me to understand the semantic and syntax and be able to process data with it, using basic functions.

I also want to highlight that I really liked "swirl" and it is a great tool to get into the subject!

Where I would encourage you to do better are:

* the slides of the ppts are in low resolution and the fonts are two small in my opionen (there are also no colours)

* Dr. Roger D. Peng did not speak that clearly and often he go muddled.

* The assignment in week 3 is pourly explained and only some further explanation in the forum could clearify the major aspects. Also it was quite unclear for me, how it is related to the learning content of week 3.

by Lisa E

Nov 22, 2017

Course lectures do not adequately prepare students for the exercises. Lectures were very basic and the programming assignments required a lot of learning beyond the lectures. By supplementing with info from other online searches i was able to learn enough to complete the assignments. I feel like I learned a lot this way-- however-- i really didn't need the course to do this. I don't feel that the course lectures added anything that i couldn't have found on the internet.

Also-- if you can't stand the sound of people swallowing and slurping when they talk-- you might want to avoid these lectures-- I couldn't stand the slurping noises this guy made when he talked!

by Julio L

Dec 02, 2016

Dr. Peng is great at teaching, and the lectures are not hard to follow. The recommended e-book is almost a transcript of the lectures' examples, and I really recommend getting it (I got it on print, as I like to make annotations while following the videos).

That being said, the Programming Assignments are extremely difficult for anyone with no programming background. The Assignments do not require just what is being taught, and demands a lot of google and stack overflow research in order to solve the problems. If you are doing other Coursera courses and/or working at the same time, I recommend you invest time in this and do not let the assignments for the weekends.

by Hani M

Jun 08, 2016

I really struggled - coming from a zero programming background. I recommend tons of reading, practical exercises, swirl is a bit of a savior and so is stackoverflow. Even with all of that, I struggled to get my mind to think like a programmer and structure the thoughts into plans for the assignments and tests. I think there needs to be a course before this that teaches one what the first step of solving a programming-related problem; eg one that focuses on flow charts, breaking down the question, etc... It literally is like learning a new language : you need to keep reading and practicing and watching/listening to others do it until you start to get it.

by Pramesh P

May 11, 2020

This is a very challenging course. The slide-based quizzes and programming assignment up till the third week are fairly easy, however, for an intermediate level course, the programming assignment on week 4 is very tough. I found much of this course more as 'R as a programming language' than as 'R for statistics and data analysis'; the latter was what I was looking for. On the positive side, the course gets into the nuts and bolts of R and gives an overview of many different aspects of R as a programming tool. All in all, I found many new things to pick up from the video lessons and programming assignments, but there are equally many rooms for improvements.

by Daisuke I

Jun 28, 2016

This course was mostly self learning. It gave me a framework to go along but what is presented in lecture and assignments are completely different. The discussion board and mentors are really good resources and can provide pointers to move along. It is definitely not a class that can provide sufficient information to learn and build applications, but the individual's effort in passing the quizzes and the projects will. It is up to the student to figure out through stack overflow, youtube, and other search result to figure out how to complete these assignments. I believe the assignments given from this class are realistic to real-world situations.

by Manish A

Jun 02, 2020

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.

by Paul M

Apr 22, 2018

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.

by William K

May 14, 2020

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.

by Dean S

Feb 01, 2018

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

by Tessa W

Feb 02, 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 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.