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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

4.6
17,394件の評価
3,641件のレビュー

コースについて

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....

人気のレビュー

MR

May 12, 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.

JM

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.

フィルター:

Rプログラミング: 76 - 100 / 3,541 レビュー

by Abhishek J

Sep 27, 2016

I will break down the review into the contents and comment on them. Before doing that and saving the trouble for people who do not like to read a lot - This course is an awesome kick-starter for R-programming.

Video Lectures : The speed and content are just perfect. The concepts covered in each lecture and the manner in which it was taught just made them stick well in my mind.

2. Quiz - They were simple so I infer that they are meant to test how well we have learnt the concepts.

3. Swirl Practice Programming Assignments - A very innovative way to teach us in the R console itself. I really enjoyed playing with it.

4. Programming Assignment - It was a sheer pleasure to do the last assignment. The level was really good. I found it a bit daunting at first but then caught up by reviewing some concepts.

5. Discussion Forums - I couldn't be very active in terms of replying but I never missed to hear what mentors had to say. I owe thanks to mentors for their awesome posts that gave deeper insights especially Al Warren.

I highly recommend this course. Prof. Peng - your videos are really good and far from boring. And yes, Thank you Coursera.

by Patricia R B D

May 23, 2018

I have long since wanted to learn R, but other online tutorial sites which mostly involved learning through copy-pasting codes didn't help me well. I had no expectations for this specific module as I know that I have unsuccessful experience on learning R online, but this module helped me significantly. Unlike other online tutorial sites, lectures in this module helped me understand how R thinks and works. Lexical scoping was particularly difficult to understand at first, and I also had to rewatch it a few times, but it did help me a lot in actually learning the language. I also like how the programming assignments are laid out as "machine problems" wherein students are asked to create functions that also require us to search for other functions on our own. The swirl exercises were also particularly helpful for me in remembering some useful functions that I would later use for the programming assignments. In just one month, I am now confident to say that I know how to R (but I know there's a lot yet to learn hahaha).

by Michael M

Jul 31, 2017

This is one of the most frustrating courses I've ever taken. Please do not mistake this for criticism, it is not. This course is basically trial by fire, but at the end of it, I am surprised how much I have learned about R. One suggestion I have for students is this: do not just write the code for the functions from the assignments. Play around with the different functions by writing your own codes. Here are some ideas: write a code that takes in two numeric values and one letter that each represent the corresponding sides of a right triangle. Your code should calculate the length of the third side using the Pythagorean theorem. Also, write a code that solves a quadratic equation in standard form given three numeric values as elements in a vector (where each element = its respective leading coefficient). Finally, write a code that takes any numeric matrix with dimension [3:n] and runs each column of the matrix through the quadratic formula. Doing this really helped my understanding of the split and lapply commands.

by Carlos C

Sep 04, 2019

Excellent course. Really. Don't listen to those people saying it is too difficult. You just need to think, probably watch again some small lecture, and probably go to the Discussion Forums (or Stack Overflow in my case to know about how to do something specific in R), to solve the Programming Assignments. It has the right level of difficulty and the instructor, Roger Peng is amazing. He's very excited about the subject and his energy helps to motivate you throughout the course.

Maybe just a little bit of programming experience is required (just thinking in programming terms or knowing the basic functions). But really, I believe anyone with motivation, patience (you're gonna need this last one haha), and focus can pass this course without a problem.

I almost didn't take this course because of the negative comments I read before starting. But trust me,take the leap and start R Programming from Johns Hopkins University. You won't regret it! Especially if you're interested in the Data Science or Data Analysis field.

by Miguel C

Mar 16, 2020

I really enjoyed this course!

I was already somewhat familiar with R but I now feel much more confident in my R programming skills. I am glad this course was not exclusively helpful for people just starting with R. I learned many new things and I sometimes struggled with some of the assignments (especially week 3 programming assignment) and they pushed me to understand more complicated concepts, which I was really happy about.

I thought the swirl library was also really helpful. It solidified what we'd learned in the video lectures, and sometimes delved into things I had not seen before or things we had seen before but with more detail, such as ellipses (as arguments in functions), definition of binary operations and simulations of coin flips.

The only part I was not interested in is the history of R at the beginning of the course. I didn't really care for it, but I think I understand why it's there.

Overall, I really enjoyed it and I would definitely recommend it to other people.

by 张万八Colin

May 10, 2020

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.

by Emre Y

Mar 25, 2020

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.

by Bruno H M d O

Jan 15, 2020

Foi um curso bem útil e de grande aplicabilidade, passando muito bem por todo conteúdo de funções, loops, extrações e manipulação de conjunto de dados, reforçando muito bem através de exercícios. Em conjunto com os principais métodos usuais de depuração, otimização e utilização de gráficos. Entretanto, achei este curso com uma dificuldade considerável nos projetos semanais para quem é iniciante, dediquei por um mês uma média de 4 horas/diária (inclusive aos finais de semana) e a maior parte do tempo gasto foi buscando conteúdos de apoio, metodologias adicionais em fóruns como o GitHub, Stackoverflow e lendo a biblioteca do R. O que não é algo ruim, pois no dia a dia, iremos nos deparar procurando novas informações e metodologias mais atuais para fazermos algo de uma forma mais eficiente.

by Edmund J L O

May 11, 2016

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.

by Zoey

Apr 30, 2018

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.

by Wei D

Aug 11, 2019

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.

by Tomohiko J M

Nov 29, 2016

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.

by Garrett F

Apr 23, 2020

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!

by Jonathan B

Dec 17, 2015

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

by Paul L

Jul 04, 2018

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.

by George G

Jun 09, 2018

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.

by Huang Y

Nov 26, 2018

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.

by VADALI S G

Nov 21, 2016

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.

by Anand K

Feb 10, 2016

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!

by Marcelo S

Sep 08, 2017

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.

by Martijn T

Jun 10, 2017

As a new programmer, I had to chew on this one for weeks and after looping through the video's over and over again eventually mastering it. The swirl exercises are absolutely essential, and so is the discussion forum (and uncle Google / hacking skills). Although frustrated occasionally - and watching others being frustrated or even giving up, I believe the entire course was set up brilliantly. From the assignments I liked the lexical scoping assignment the least. Would have been nice to be replaced by something little bit more encouraging.

by Christopher R

Feb 02, 2017

I finished this last year with a good background already in R. However, this course took a lot of time, a lot of stackoverflow searching and generally a lot of work! Now that I'm a year removed from the course, I can say that it's been one of the better, more rigorous, more practical and more applicable courses i've taken. I still spend A GREAT DEAL of my time looking for answers online but now the questions and tasks are much more complex now that I've taken my programming skills to higher levels, with lots of thanks to this course!

by Deleted A

Mar 15, 2016

The Data Science specialisation with John Hopkins University is definitely worthwhile and, as a relative novice in the area, I'd highly rate and recommend R Programming. The lecturer Mr Peng presents the information in a clear and concise way, conducting walk-throughs of different steps, and providing opportunity for practice exercises. As well, the accompanying book published by the lecturer, learning materials, mentor Mr Warren and discussion board are invaluable for beginners like myself. Thank you for a terrific course so far.

by Chuanhui L

Sep 29, 2016

Well-organized R programming course for academic amateur with some OOP knowledge before! By simply using Rgui, th is class focuses on techniques in ABC's of R programming including not limited to basci objects, data strcuture, controlling sentences, I/O and debugging suggestions.

Personally, I take this course for job purpose, but this course falls short for industrial techniques, such as reading/outputting excel, sophiticated operation on data frame, or combining R with Python and SQL.

Hope that this comment will be useful to you.

by Volodymyr C

Nov 23, 2018

Lectures are well-presented and programming assignments are engaging (but they took me about eight hours to do each week). Swirl was a great tool for getting to grips with how to use the functions discussed. Definitely recommend having a pen and pad with you to take notes throughout - have no idea how the course could be done without doing this. Overall, I found it an engaging and suitably-challenging course for someone new to R , and with a little tweaking of programming assignment 3, I think it could be an industry standard.