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Avis et commentaires pour d'étudiants pour The R Programming Environment par Université Johns-Hopkins

998 évaluations
271 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


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.


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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126 - 150 sur 266 Avis pour The R Programming Environment

par Carlos A A F

Sep 27, 2017

It was an excellent course.!

par Kasidis S

Jun 03, 2019

Good introduction, love it!

par Dennis M S

Oct 17, 2016

Superb advanced R course.

par savinay s

May 29, 2018

Good basic course for R

par Mikhail K

Jan 26, 2018

I like the way it goes!

par Alicia B

Oct 15, 2017

Great intro to TidyR!

par Xueqi Q

Jul 03, 2020

I like the swirl !

par Gustavo D

Mar 09, 2018

Excelente curso!!!

par Isaiah M

Aug 22, 2018

Very challenging!

par Yan L

Dec 15, 2016


par Edisson Q L

Nov 10, 2018

Excelent course!


Nov 07, 2017

Excellent course

par Tamás B

Nov 26, 2016

Perfect Course!

par Yifei L

Oct 14, 2018

Great class!!


Oct 27, 2017

Great Course

par Le D A

Mar 19, 2020

Very useful

par Arthur C

Feb 10, 2018

Nice course

par Francisco A M

Feb 22, 2018


par Rodrigo G G

Mar 06, 2017


par Marcelo B

Aug 04, 2017

Very Good

par Rebecca A D

Sep 24, 2017

good one

par Ganapathi N K

May 13, 2018


par Benjamin S

May 14, 2019


par Dmitry S

Oct 01, 2016

+: I reached my goal for the course and now I understand a bit about R. I succeeded to pass within much shorter time than anticipated course duration. The course certificate is posted to my Linkedin profile.

-: No human mentors on the course discussion forum - all questions answered by other students. Automatic tests in swirl are too restrictive and do not accept perfectly correct student solutions slightly different to those anticipated by the authors. Week 2 assignment is much different from the reading material. Nothing taught about charting in R.

Overall comment: I think it is good value for money.

par wally

Jan 26, 2017

All in all good stuff. A couple of comments:

Swirl grading should be a little more flexible; sure cut is more succinct that nested ifelse's, but there's more than one way to skin the data-analytic cat in R, as I'm sure y'all are aware.

Also, I recommend more emphasis on data tables. I use them exclusively due to the dramatic performance improvement over data frames. And in my brief experiments, dplyr and tidyr commands worked on them too.

This first course was review for me. Nonetheless I definitely learned a few practical things that will up my data science game (which can always use upping).