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The R Programming Environment(으)로 돌아가기

존스홉킨스대학교의 The R Programming Environment 학습자 리뷰 및 피드백

983개의 평가
265개의 리뷰

강좌 소개

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....

최상위 리뷰


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.

필터링 기준:

The R Programming Environment의 259개 리뷰 중 126~150

교육 기관: Kasidis S

Jun 03, 2019

Good introduction, love it!

교육 기관: Dennis M S

Oct 17, 2016

Superb advanced R course.

교육 기관: savinay s

May 29, 2018

Good basic course for R

교육 기관: Mikhail K

Jan 26, 2018

I like the way it goes!

교육 기관: Alicia B

Oct 15, 2017

Great intro to TidyR!

교육 기관: Xueqi Q

Jul 03, 2020

I like the swirl !

교육 기관: Gustavo D

Mar 09, 2018

Excelente curso!!!

교육 기관: Isaiah M

Aug 22, 2018

Very challenging!

교육 기관: Yan L

Dec 15, 2016


교육 기관: Edisson Q L

Nov 10, 2018

Excelent course!

교육 기관: GERALDO A

Nov 07, 2017

Excellent course

교육 기관: Tamás B

Nov 26, 2016

Perfect Course!

교육 기관: Yifei L

Oct 14, 2018

Great class!!

교육 기관: JEEWESH K J

Oct 27, 2017

Great Course

교육 기관: Le D A

Mar 19, 2020

Very useful

교육 기관: Arthur C

Feb 10, 2018

Nice course

교육 기관: Francisco A M

Feb 22, 2018


교육 기관: Rodrigo G G

Mar 06, 2017


교육 기관: Marcelo B

Aug 04, 2017

Very Good

교육 기관: Rebecca A D

Sep 24, 2017

good one

교육 기관: Ganapathi N K

May 13, 2018


교육 기관: Benjamin S

May 14, 2019


교육 기관: 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.

교육 기관: 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).

교육 기관: Bryan D

Jan 14, 2018

There are a few areas of the course that are not fully explained and cause extra time trying to 'figure it out'. I am not referring to code/learning, but the logistics of the class. However, there are a few questions in assignments & quizzes that refer to things that were not particularly explained either in the lecture or in the book. I understand self study is beneficial, but I start the course with the understanding that questions will be based off of lecture or the book. If additional resources are needed, then that should be expressly stated in the lecture or book.