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

4.6
étoiles
17,394 évaluations
3,641 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

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.

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!

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51 - 75 sur 3,537 Avis pour La programmation en R

par Alejandro M

May 25, 2020

The course is too ambitious and some themes are explained in a very plain and boring way. I can't say you will learn nothing, the course isn't too bad, but if you have no prior experience with programming o even if you have but not in R, the course programming assignments will be a little difficult and the material. If you want to complete this course you will have to invest a lot of time searching for things and/or waiting for help in the forums. 5/10

par Suwei W

Jan 02, 2019

I learned something, of course, in this course. But without previous experience in data science, I found it OK to understand the lectures, but always got lost in the coding assignments. I tried to finish it on my own, but it turns out I have to search everything online. I felt that there's a big gap between lectures and assignments.

par El M

Apr 09, 2019

very good course but you need much more time then announced to finish the assignments

par Jueyi S

Jan 07, 2019

Tutorials are indispensible for students to complete the assignments.

par Sherif A

Jan 01, 2019

Needs to be more interactive

par SANJAY K V

May 08, 2020

I believe many of the students taking this course might not have any prior coding experience. Personally, I found the assignments quite challenging (rather than intellectually stimulating or providing learning) as many of the issues and syntax used in the assignments were never elaborated in depth in the videos. There may be a few people with really good statistical and coding background, who may not find this review much helpful, But, being new to coding, I can understand this and I believe the people who really need this course to equip themselves with these lessons may not be adept at solving some of the problems asked in the assignments. Please take this constructive feedback into consideration while modifying this course (if you do so). Otherwise, it was a wonderful course and gave same basics to build a foundation in R. Thank you.

par Juergen K

May 21, 2020

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!

par Tareq R

Sep 17, 2018

I think for a MOOC, this course could have used the power of video a lot more, listening to the videos that are basically voice over a slide , wasn't helpful at all, and if it wasn't for the book, I wouldn't learn anything.... if the videos were more illustrative and visual to explain certain concepts , that would have been much better

par Javier P

Dec 08, 2019

Very poor material. Very theoric, no interaction, interesting applications or examples, and very boring lectures.

The material is very trivial, without real applications.

The assessments were useful but in some cases they were not related with the topic.

par Kristofer R

Oct 31, 2018

R Programming assignments were much more complex than what the tutorials taught. There was a very drastic jump between the two and was very difficult/frustrating to complete, especially for someone with no coding experience.

par Rushabh K

Apr 28, 2020

Should have been better taught and the stuff in assignment is way tough than taught in the lecture

par Tural D

Dec 14, 2019

My overall evaluation for that course is 1 stas due to main two reasons:

First of all course has too much information without the applying during the weeks. However once a learner opens the assignment it is inevitable to face with very hard tasks

I spent more time on youtube and other sources to learn how to use the functions and solve the assignments in comparison with the course itself. That is the reason I am not satisfied with the course.

Given theory is okay but the applying of them during the week is very less. THat is the reason learner face big issues during quizzes.

I found SWIRL assignments very useful that I can say they were the only things that I learned the practical part of R programming.

My advice is to increase the number of SWIRL assignments and increase the difficulty level of them each time.

It is also better to decrease the difficulty level of assignments and quizzes. Because course is more theoretical than being practical in teaching. but the assignment requirements are more practical.

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 Rob E

May 21, 2020

Roger Peng is regarded as one of the best in the business when it comes to practicing data science, but I found his instruction skills wanting. As someone new to R and new to programming, I found him somewhat hard to follow at times. Nevertheless, I powered through. Unfortunately, when I came to the quiz at the end of Week 2, I found it was drawing on background knowledge that had not been taught in the course. Honestly, unless you're starting with a background in programming, I would not recommend this course.

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 Todd D

Apr 24, 2020

This course is frustratingly bad. The lecture topics are very scattered and provide almost no practical information. The slides are static with simultaneously too much and too little to understand how to apply them "in the real world." The disparity between the lecture material and assignments is truly laughable and -- if you are a beginner -- more or less impossible to complete without lots of Google/stackoverflow searching and head scratching. I would not recommend this to anyone.

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 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 Rimoun G A F

May 05, 2020

the lectures are very shallow and lack good code examples. The programming assignments are too hard. The worst course I have ever seen.

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