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ジョンズ・ホプキンズ大学(Johns Hopkins University) による The R Programming Environment の受講者のレビューおよびフィードバック

4.4
896件の評価
235件のレビュー

コースについて

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....

人気のレビュー

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.

KV

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.

フィルター:

The R Programming Environment: 151 - 175 / 231 レビュー

by Jhosse P M R

Feb 04, 2017

Excelent course to start with the basics of R language. It gives a modern introduction to R programming avoiding traditional topics like loops and conditionals keeping them for more advanced programming topics. It also covers almost all tidyverse packages with a shallow introduction to the most common packages.

I have acomplaint. The dataset for the final quiz was outdated, I managed to pass the quiz guessing variable names.

by 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).

by Johans A A

Feb 01, 2018

Exccellent Course! I really enjoyed it!

by RIPUNJOY G

Jan 04, 2017

Could have been better. Expected some interaction/videos from the mentors.

by Fernando J N

Jan 09, 2018

Very informative, however could be more complete. Some functions aren't introduced and the swirl package didn't accept other solutions path that would likewise lead to the same result. I believe also that some update would not harm. However, this course is really informative and, in my opinion, one of the best available. I really enjoy this course. Nice job and thank you very for sharing this knowledge.

by Omar E

Feb 04, 2018

I liked the swirl() package a lot, made me jump into writing codes into RStudio straight away. My only wish was to have some videos that would push me further

by Eugene W

Feb 21, 2017

The material gets progressively tougher but I never felt totally overwhelmed. My only feedback is for the mentors to be more responsive in the forums - if we're posting it means we've already thrown everything at the question and still couldn't figure it out.

by Karl M

Feb 24, 2017

This is a good introduction to R but I do wonder if there could be a little more content, particularly in week 4.

by Nashit A

Jul 21, 2017

Swirl should be accepting of other answers as well as different snippets of code will produce the same result.

At times this got frustrating and my reason of taking time to complete the course is because I'd leave things in between because of swirl issues.

This goes away and it is a 5-star as a beginner course; it is made beautifully to get us up to speed

by Matthew D

Aug 21, 2017

The course is great, and very challenging. It is a little frustrating that the course requires 1 out of 2 programming assignments to be completed, but shows you as past due despite reaching that goal...

Getting this corrected and verified by Coursera has also been difficult.

by Halil K

Dec 31, 2017

The last quiz is super hard and makes you feel a bit unprepared. But overall I learned a lot from this course

by 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.

by Jing L

Jun 20, 2017

Useful, but it is all text so the course is not very fun

by Jenny T

Jul 13, 2017

I think that the explanation of the material should be adopted to people that are not programmers

by Almira Y

Mar 29, 2018

English is not my native language so i had troubles with tasks, because it is sometimes

hard to understand what you have to do. My advice - rewrite final quiz and make it more easy for understanding.

by Kevin K

May 09, 2018

Learn basics and some good data science tools.

by Gregory H

Dec 18, 2017

Very good overall. I feel that the first weeks are too easy relative to the last week - more involved practice and exercises would have been good before getting to the final quiz.

by Rohit S

May 05, 2018

It's a great course for those who are just starting to learn R, It provides enriching for data analysis, however as a constructive feedback, I feel there could be improvements around how the exercise are planned and the submission process for the exercises

by Francesco D Z

May 19, 2017

Very good starting course, covers all the basics.

My 2 cents: I would prefer more tests like the last one than the swirl lessons, they're more challenging thus you learn more.

by James L

Apr 26, 2017

Excellent intro to using Tidyverse (dplyr, tidyr, readr) to manipulate and clean data in R. Occasionally the readings and the SWIRL homework don't quite match up, but it's not a dealbreaker by any means. It was definitely worth my time overall.

by Sunetra S

Jan 08, 2017

Course is good. However, some of the packages discussed in the examples, such as ggplot etc. should be discussed in more detail.

by chengchenggan

Dec 09, 2017

the last exam is very hard, which need more knowledge than what you learned in previous chapter. the forum is not very helpful. lots questions are either not answered or answered with delay. But overall, you can get the basic concept from the course.

by Kevin D

Jul 10, 2017

Une initiation intéressante et complète à R qui a l'avantage de donner des bons réflexes pour coder rapidement. Le caractère interactif des exercices de programmation est un gros plus. Attention : il n'y a pas de vidéos hormis la vidéo d'introduction. On peut aussi avoir des difficultés de syntaxe susceptibles de nous bloquer un bout de temps, notamment sur des fonctions où la documentation est un peu aride (je pense à cut et à spread sur lesquelles j'ai bien passé 1/4 du temps que j'ai consacré au total à ce MOOC).

by Michael C

Jul 27, 2017

I like the swirl exercises, but found the text lessons to be very short. Overall, good but I hope some video will be given in future modules.

by Wen H

Jan 05, 2017

A very nice introduction to the R programming environment. I learned a lot and it was fun to do!