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Opiniones y comentarios de aprendices correspondientes a The R Programming Environment por parte de Universidad Johns Hopkins

4.3
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1,115 calificaciones
308 reseña

Acerca del 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....

Principales reseñas

MV
25 de dic. de 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
17 de jun. de 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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251 - 275 de 303 revisiones para The R Programming Environment

por Tristan C

15 de may. de 2018

You can learn most of it through the package swirl but the quiz at the end was a rewarding challenge that gave good practice. Would make it much better if it had video tutorials however

por Hardik S

25 de oct. de 2017

This is a fairly good course.The interactive R environment is a little rigid and acknowledges correct answers only when certain specific codes are used but all in all .its good

por Prakhar P

13 de may. de 2019

This is a refresher course for someone who already knows R. For anyone starting to learn R and Data Science, Data Science Specialization is a good curriculum to start with.

por Juan A

15 de feb. de 2017

The instructors did nothing. They did not even respond to a single question through the entirety of the course. The information in the readings was helpful though.

por John E

11 de dic. de 2017

If I didn't already have experience in R, and with tidyR in particular, I'm not sure this course would have been that helpful. As it was, it was a good review.

por Hans H

15 de mar. de 2017

One must have some R knowledge prior to take this course. I would recommend to take the other R programming course from the Data Science track before.

por Pedro J O

22 de mar. de 2018

The use of swirl proved to be confusing to do week 2 test. I had to read the comment threads to figure out which subjects were needed for the quiz.

por KEVIN A F

8 de jul. de 2019

The course difficulty abruptly increased in the last week.Especially with the last quiz. A swirl exercise before the quiz would have been helpful.

por Daniel V

8 de nov. de 2020

Quick and easy introduction to R. Doesn't go into any depth, no videos and not very challenging assignments. Would not recommend.

por virginia b

2 de oct. de 2018

Wrong tutorial on swirl that obliges you to follow the course twice to get the code for the quix and to take the points to go on

por Harsh D

21 de mar. de 2018

Less practice items in this course. Majority is theory. Would have preferred if it had a some more practice material.

por Nate W

26 de sep. de 2019

low production value at times, frustrating errors in the course data and instructions, but got me there in the end

por KEVIN E A C

30 de abr. de 2017

It was very dificul, i think yoou need to improve the example you give the the students and be more interactive

por Feng J

18 de jun. de 2017

The problem set is well-designed but the prompt and the wording could be misleading for non-native speakers.

por Andisheh P

13 de jul. de 2017

The final assignment is suddenly much more difficult than the rest of the course, otherwise a good course

por Haoyu Z

28 de abr. de 2017

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

por Nick B

1 de nov. de 2017

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

por Vrushali C

3 de ene. de 2021

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

por George E C

26 de abr. de 2020

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

por Geoffrey S R

5 de oct. de 2021

Needs more discussion and extensive practice problems.

por Saif A K

15 de abr. de 2018

good course ,, but alot of readings :(

por Jan K

8 de nov. de 2017

A little too easy for the certificate.

por Luca B

12 de may. de 2020

It was n't so easy

por Kayley A

22 de mar. de 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.

por Jessica G

7 de may. de 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.