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Learner Reviews & Feedback for The R Programming Environment by Johns Hopkins University

4.3
stars
1,157 ratings

About the Course

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....

Top reviews

MV

Dec 25, 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 17, 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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276 - 300 of 319 Reviews for The R Programming Environment

By Haoyu Z

Apr 28, 2017

The instruction from the first three weeks does not sufficiently prepare me for the final project.

By Nick B

Oct 31, 2017

There HAS to be mentors/instructors around to assist with syntax questions during this process.

By Vrushali C

Jan 3, 2021

some assignment questions are not from the lessons. please solve this issue .

By George E C

Apr 26, 2020

Good course, but in serious need of updating and proofreading.

By Saif A K

Apr 15, 2018

good course ,, but alot of readings :(

By Jan K

Nov 8, 2017

A little too easy for the certificate.

By Luca B

May 12, 2020

It was n't so easy

By 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.

By Jessica G

May 7, 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.

By Jonathan K

Aug 17, 2021

While I do feel like I learned the material, the lack of video demonstrations and over-reliance on the textbook made this a much less pleasant class than most Coursera courses. In addition, the demonstrations of ideas were generally weak - in particular, the final quiz, where we were expected to combine datasets, was something that I didn't feel prepared for. It felt like I had to teach myself how to do this through my own research, rather than something that the class had prepared me for.

By 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.

By 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.

By Matthew C

Oct 1, 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.

By Dzmitry M

Oct 4, 2021

Swirl is messy. There is no version control, and the package does not handle the course's previous versions well.

Swirl believes that 1:3 and seq(1,3) produce different outputs. Also, it does not tolerate -c(1,3) instead of c(-1, -3).

The submission of the quiz results is buggy. Overall, text-based courses do not seem to be elaborate enough.

By Daniel M

Nov 15, 2021

Several features are currently not working. For example, the Swirl assignment in week one has a bug whereby "R" doesn't accept the computer assignment code generated by Coursera. I can't submit the assignment for a grade. A few people have commented on the discussion board, but there is no response to this from the instructors/TAs.

By Erik R

Jun 11, 2020

99% of this course is awesome, but there's a VERY well-documented issue with the Week 2 assignment that took longer than the rest of the course combined. An official solution from the instructors is necessary, though students are quite helpful. That one issue heavily distracted from being able to effectively learn.

By 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.

By Trenton H

Apr 4, 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.

By 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/

By Alvaro O

Jul 14, 2020

The course material is pretty good, but Swirl is terrible, and its integration into Coursera is even worse. I can't recommend this course.

By 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..

By Glendronach 3

Aug 7, 2020

The R Programming Environment is very buggy. Please tidy up the errors and make it more user-friendly.

By Alexander H

May 15, 2018

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

By Shangwen Y

Nov 25, 2023

It covers basic concept of R, but less practices and tutoring

By Rovishen R

May 25, 2022

Tasks submision doesn't work. No reaction from lecturers