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The R Programming Environment, Universidade Johns Hopkins

4.4
791 classificações
209 avaliações

Informações sobre o curso

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....

Melhores avaliações

por 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.

por VS

May 28, 2017

Good Practice..........!!!...really helpful for building data science concept through R Programming.........Really salute for hardworking of instructor..................!!!

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203 avaliações

por Bharath k Reddy

Apr 14, 2019

One of the best courses for R

por David Miller

Mar 25, 2019

The content is good, but many students (including me) are NOT able to submit assignments with the course "token". I've commented in the course discussion forum about this, and I have opened a support ticket with Coursera, but no one is taking serious initiative to correct the malfunction.

por Vikesh Koul

Mar 21, 2019

Very good course. The pedagogy and the course content along with the assignments is rigorous and fantastic.

por Marcinina Alvaran

Mar 18, 2019

The course content itself is good and easy to follow, but one assignment has a recurring bug since at least 2 years back that prevents other students from successfully submitting a required assignment. Despite a long and active thread regarding this bug, the problem has yet to be addressed, preventing some students from completing the course.

por Georgios Papadopoulos

Mar 15, 2019

Neat and easy to read introduction!

por Laura Ortega

Feb 27, 2019

The contents of the Course are great and you can learn a lot of stuff regarding the R Programming Environment. Unfortunately, there has been errors in the evaluations that have been pointed out in the forum for more than two years now and the Instructors haven´t attended them. They claim that that´s the system of Johns Hopkins University, to make evaluations hard, however, when you refer in a test to the name of a variable that doesn’t exist is not making a test hard, is losing the time of your students and therefore adding unnecessary obstacles to their learning process. Also when comparing the material printed in Coursera and the book that the instructors suggested for the Course, there are basic errors like printing the wrong Graph. If you are really interested in advanced programming in R, take the course, however, BE AWARE THAT THERE ARE FLAWS AND READ THE FORUMS BEFORE ANSWERING THE EVALUATION, IF NOT YOU ARE GOING TO WASTE A LOT OF TIME IN USELESS ISSUES!!!!!!

por Vibha Sharma

Feb 14, 2019

The course was well designed for beginners. It helped me to gain lot of confidence in building my knowledge

por Alice MacQueen

Feb 01, 2019

Solid introduction to R and the tidyverse with very nice assignments to get practice on the command line.

por Tianyuan Wang

Jan 27, 2019

It is a very good course for new learners. However, it could be better if there is a R script writing the right code for the final quiz.

por Yang Zhengyu

Jan 26, 2019

Very practical course with plenty of practices to get you started data handling in R. Course focus on Tidyverse series of packages which come in handy when dealt with data manipulation. Little is talked about on in-built functions of R and use of functions is not covered.