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Avis et commentaires pour d'étudiants pour La programmation en R par Université Johns-Hopkins

4.6
étoiles
15,949 évaluations
3,261 avis

À propos du cours

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....

Meilleurs avis

WH

Feb 03, 2016

"R Programming" forces you to dive in deep.\n\nThese skills serve as a strong basis for the rest of the data science specialization.\n\nMaterial is in depth, but presented clearly. Highly recommended!

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.

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51 - 75 sur 3,152 Avis pour La programmation en R

par Benjamin L

Dec 06, 2018

Don't expect so much... Lexical scoping will probably not be used by the majority of data scientists but the course expects you to research it yourself entirely and spend hours on hours on it, when the focus could have been placed on somewhere else!

"Mentors" are quick to respond to dissatisfaction at the course with comebacks but when students ask for help regarding assignments they are nowhere to be seen.

Watch all the lectures, enrol for 7 day trial, submit assignment 2 and 4, and ignore the rest. Don't let them trick your money!!! (PS I was like you at the beginning, I thought of paying for the course, doing a good job and getting a certificate, but trust me, this course is not worth it.)

par Lorena M M

Dec 01, 2019

The lectures are not very engaging, just listening to someone talk about a code is not a good way to learn how to do it. The swirl course is a better option, but it is very basic and in most cases it consists only in copying something that's already on the screen. The gap between what you are taught in the lectures and the assignments is absolutely abysmal and incredibly frustrating. How are we supposed to know how to create complicated functions after just listening to someone say what a function is? I don't think that teaching someone the equivalent to "2+2=4" and then asking them to solve Riemann's Hypothesis in the exam is very fair.

I would not recommend this course.

par Troy M

Dec 05, 2019

As many others have stated before, the gap between the lectures/swirl practices and the actual assignments is way too big. I am a novice at R but did come with practice of the basics before starting this course. I also took notes and completed every swirl practice. Even with that I felt incredibly unprepared for the assignments. I understand that searching the internet for help is part of the process but the extent to which the student must search is unforgivable for this to be considered a proper way of teaching. I would also caution that the estimated hours of completion are understated if you plan on trying to actually complete these assignments by yourself.

par Dilip A

Dec 23, 2019

The instructor appears unprepared to present the material. When presenting it appears that it's the first time he is reviewing the material.

This is my first bad experience on Coursera. The last Coursera course I took (SQL for Data Science by University of California, Davis) was great as it appeared that the instructor was prepared with what they were going to present.

Coursera needs to vet their instructors' course recordings before allowing them to put forth their material on the site.

par Olivier P

Mar 13, 2016

This is probably the most pedagogically inept course I have ever enrolled on. Although the content is what you would hope to find in such a course, the delivery of it is outrageously bad. When to complete your assignment, Google becomes your best friend rather than your lecture notes, you know that something is wrong. The idea that a baby thrown in the water may just learn to swim rather than drown is pedagogically retarded. Unfortunately, this seems to be the approach here...

par Ethan T

Jun 08, 2019

The gap between tutorials and assignments is huge. They teach you algebra I and then expect calculus. I got by because of google searching. It took a long time, and it was very frustrating. This course could have been better if there were intermediate assignments to help close that gap. I'm not sure why they've done this already. Based on the discussion sections, I can tell that a large percentage of people quit the data science specialization after taking this course.

par Julio G D

Feb 06, 2017

Honestly, I'm very disappointed with this course. The content taught in this course is not in accordance with the assignments. It is like someone taught to be a builder and asked to build the Brooklyn Bridge ... Not fair at all.

If you are going to ask to build a bridge, teach me how. If you teach me how to be a builder ask me for a wall, not a bridge.

par arif v

Jan 26, 2019

the content of the course is rather irrelevant of the assignments, at least in terms of the hardness... also the presenter is substantially fast.

par wang z

Nov 19, 2017

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。

par Akram A

Jan 31, 2019

it's not good to explain only without practice or giving examples

par Ramalakshmanan S P

Feb 23, 2016

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

par 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.

par 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).

par 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.

par 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.

par 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.

par Carlos M

Aug 23, 2016

Difficult at times, I regularly used outside websites like stackoverflow to help with assignments, but that's how the real world works, there's no way that the lectures could solve all your problems.

Favorite: writing my own functions that searched real databases and returned means, ranks, and useful info. I felt like I took a huge step forward in my goal for data science.

Least favorite: Assignment #2, it felt completely unrelated to anything I learned, I wasted hours just to find out it was redundantly simple and in the end I didn't even find out if my code worked, the grade was peer-reviewed based on if you could correctly upload it to github and if it "looked" like it would work. (How would I know! LOL, I assumed all my peers' code was good enough)

Would 100% take this course again.

par 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.

par 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.

par 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.

par 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.

par 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

par 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.

par 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.

par 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.