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Learner Reviews & Feedback for R Programming by Johns Hopkins University

4.5
stars
22,339 ratings

About the Course

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....

Top reviews

AB

Sep 6, 2017

Great course for people who work with data a lot. This course actually helps in looking at data in its basic forms, helps understand transformations better, and gives ideas about playing with it.

RD

Mar 2, 2016

A great introduction to slightly more complicated R programming. Basic concepts covered well and it builds nicely to the point where you feel like you can apply your knowledge to real world examples

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3426 - 3450 of 4,750 Reviews for R Programming

By Rodrigo P G

Apr 18, 2016

Nice course and interesting material but the other students evaluation is quite subjective.

By Dushan Y

Mar 30, 2016

Good fundamental overview of the programming language. I also liked the pace of the course.

By Shaurya S

Sep 7, 2020

can do with more practical real life examples/ case study.

Swirl was a great tool to learn.

By Rishabh T

Mar 31, 2019

Good content, videos are very useful. Also the swirl() exercises are best way to practice.

By Himanshu S

Feb 24, 2019

excellent course for the beginner. best part is that swirl is also included in the course.

By Angel M

Nov 6, 2020

The Swirl exercise are the best and more recomended part of the course! I learn a lot :D.

By KANTARIA M H

May 28, 2020

Sometimes I felt little bit hard assignments in comparison of contents covered in videos.

By Laurent R

Mar 31, 2019

This course is great, I loved the topics. However, the last assignement is a bit to hard.

By Himanshu C

Apr 5, 2018

Very Good Coursera. Would Recommend Anyone who is pursuing acareer in R and Data Science.

By Ian S

Jun 29, 2016

Good exercises and challenging course, but very hard if you do not know any R beforehand.

By Julio C R N

Jul 16, 2020

great explanations. A bit tiresome but because it goes into great details on the basics.

By Chih-Wei P

Aug 26, 2016

It would be nice if you could combine the lecture notes into a single file for download.

By Camila R M

Apr 10, 2021

Programming Assignments were not at the same level as the material taught in the course

By KSHITIJ S C

Sep 2, 2020

Great course! Would definitely recommend to those who want to start data analysis in R!

By Jingyuan “ Z

May 10, 2019

Homeworks and assignments are sometimes harder than what can be found in the textbooks.

By Gourav B

Jul 4, 2018

Course is very good for beginners and will definitely enhance your R programming style.

By John K

Jun 27, 2017

Great material and lectures, but a little advanced programming exercises for beginners.

By Jeyalakshmi S

May 14, 2016

Very much helpful to understand the basic about the R programming. Very well structured

By Martin S R

May 8, 2020

Teaching-wise it was great, but the materials for the assignments were too complicated

By Heather G

Mar 20, 2016

I'm a fairly experienced R programmer and still learned a few things from this course!

By Sushmita G

Mar 2, 2016

Great start to get into data analysis. A little difficult for 4 weeks, but manageable.

By Mehmet B

Oct 4, 2020

Thank you. It was a great course. I believe more emphasis on splitting is essential.

By Sohan A

Mar 10, 2020

Sometimes function appears to be hard for assignment. All other things are excellent.

By Hao X

Jun 7, 2018

Basically rewarding, but there exists a big gap between the lectures and assignments.

By Waldemar T

Jun 12, 2017

Tough course but highly interesting, enabling a better approach to data manipulation.