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Avis et commentaires pour l'étudiant pour The R Programming Environment par Université Johns-Hopkins

4.4
890 notes
232 avis

À propos du cours

This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings. As the first course in the Specialization, the course provides the essential foundation of R needed for the following courses. We cover basic R concepts and language fundamentals, key concepts like tidy data and related "tidyverse" tools, processing and manipulation of complex and large datasets, handling textual data, and basic data science tasks. Upon completing this course, learners will have fluency at the R console and will be able to create tidy datasets from a wide range of possible data sources....

Meilleurs avis

MV

Dec 26, 2018

Very Very Rigorous Course for a beginner on R language and because of its nature, after completing just one course, I feel like I have gained a lot of knowledge and also familiarity with R language.

KV

Jun 18, 2019

A very good course to read and get the valuable content of R language. This is for the students who want to learn and practice the basic and some intermediate concepts of data manipulation.

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201 - 225 sur 226 Examens pour The R Programming Environment

par Tristan C

May 15, 2018

You can learn most of it through the package swirl but the quiz at the end was a rewarding challenge that gave good practice. Would make it much better if it had video tutorials however

par Hans H

Mar 15, 2017

One must have some R knowledge prior to take this course. I would recommend to take the other R programming course from the Data Science track before.

par Luciano P

Nov 26, 2017

This course provides an amazing learning path for people who don't know R. Week by week examinations and work in the Studio environment are great to keep learning in a proactive way. The book has a huge amount of info and it is perfect for approaching R. Just I think the level required for final examination is way higher than what it was very well taught during the course.

par Pedro J O

Mar 22, 2018

The use of swirl proved to be confusing to do week 2 test. I had to read the comment threads to figure out which subjects were needed for the quiz.

par Jan K

Nov 08, 2017

A little too easy for the certificate.

par Hardik S

Oct 25, 2017

This is a fairly good course.The interactive R environment is a little rigid and acknowledges correct answers only when certain specific codes are used but all in all .its good

par KEVIN E A C

Apr 30, 2017

It was very dificul, i think yoou need to improve the example you give the the students and be more interactive

par Juan A

Feb 15, 2017

The instructors did nothing. They did not even respond to a single question through the entirety of the course. The information in the readings was helpful though.

par Saif A K

Apr 15, 2018

good course ,, but alot of readings :(

par Prakhar P

May 14, 2019

This is a refresher course for someone who already knows R. For anyone starting to learn R and Data Science, Data Science Specialization is a good curriculum to start with.

par KEVIN A F

Jul 08, 2019

The course difficulty abruptly increased in the last week.Especially with the last quiz. A swirl exercise before the quiz would have been helpful.

par Nate W

Sep 26, 2019

low production value at times, frustrating errors in the course data and instructions, but got me there in the end

par Tim L

Sep 05, 2019

There are a lot of typos, spelling errors, and oftentimes you need to do your fair share of StackExchange, forum, or book research to get an answer. I learned a lot, I just wish it was better organized. You'll learn more experimenting yourself than you will from the class.

par Craig N

Oct 11, 2019

While I learned much from this course, I would say that the readings contained enough type-o's and broken links that it became slightly annoying. Also, the final Quiz was much more difficult than the readings/practice that came before it.

par Matthew C

Oct 01, 2018

Swirl is a great idea, but each section is submitted independently of the others. You have to complete all sections in one sitting if you plan to submit electronically. I had to redo 8 of the 9 sections in week 1 for this reason.

Content-wise, the quiz in week four is significantly more difficult than the other assignments and I felt a little underprepared.

par Alexander D H

May 15, 2018

Felt lost during the final, the course was not well suited to the end quiz

par Trenton H

Apr 04, 2017

There's not much substance. Also, considering there is not video the course seems very non-interactive. Its nice to see the instructors speak and work through examples. Hoping this course was just a quick primer for the R newbies.

par Zdenek K

Nov 15, 2016

The first course of the specialization is very simple. The specialization was announced to be on an intermediate level but at the same time, you need to spend money on a very basic course with swirl assignments pretty much copying the course content. The good thing is that it includes very modern approaches to data analysis and new packages. The second course is much better, nevertheless.

par Paul H

Oct 28, 2017

I found the final project very very difficult as weeks 1 to 3 did not cover sufficient practice of the libraries which were to be used. That having been said, the project was achievable when you spent 20 hours on it. I posted several questions to the forum and received no answers.

par Teresa O

Jun 10, 2017

This was a terrible course. It starts off extremely basic in Week 1 which makes you feel like a rock star. Week 2 becomes extremely difficult then Week 3 easy again. Week 4 ends up being nearly impossible. I find that there is foundational material that the course does not cover. Nor does it provide guidance or familiarity with the material that it then tests you on. You end up having to do a lot of googling for functions to learn certain rules. It isn't designed well.

par savvas s

Aug 28, 2017

just links to a webpage... no support from the mentors no support form coursera... you can use your money more wisely..

par Arthur G

Jun 14, 2017

Too basic.

par Kayley A

Mar 22, 2018

This course has some useful information, but it is far from polished, and it is unclear who the class is truly designed for. The readings have a number of formatting issue and typos. I was disappointed that this class did not utilize lecture videos or practice exercises. There is not enough opportunity to reinforce the material through practice, which turns the assessments into abrupt roadblocks. If I wanted to spend most of my time just reading about R, I could have bought a book instead. Compared to other courses I have taken on Coursera, this class had fewer features, less content, and seemed much less thought out.

par BenT

Jul 11, 2018

The free book R for Data Science by Garrett Grolemund andHadley Wickham is a much better structured introduction! see http://r4ds.had.co.nz/

par Jessica G

May 07, 2018

This was a nice introduction to R for someone who has had previous programming experience. However, many of the lessons had simple grammatical errors in them, which is just unprofessional. Many of the swirl lessons were just the online material repeated, so reading the lessons then doing the swirl lesson was massive repetition. Also, many of the swirl "lessons" were merely "Type this in and see what happens!" which doesn't really teach anything. Finally, the final quiz material had spaces in the column headings which was fixable but added a level of monotony and inconvenience that was not needed.