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学生对 Johns Hopkins University 提供的 R Programming 的评价和反馈

4.5
22,350 个评分

课程概述

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....

热门审阅

AK

May 26, 2017

This was very engaging, however, the level of expectation and effort needed is much greater than course 1 - ToolBox.This is perhaps the best course on R Programming designed for a small duration.

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.

筛选依据:

3426 - R Programming 的 3450 个评论(共 4,751 个)

创建者 Rodrigo P G

Apr 18, 2016

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

创建者 Dushan Y

Mar 30, 2016

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

创建者 Shaurya S

Sep 7, 2020

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

Swirl was a great tool to learn.

创建者 Rishabh T

Mar 31, 2019

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

创建者 Himanshu S

Feb 24, 2019

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

创建者 Angel M

Nov 6, 2020

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

创建者 KANTARIA M H

May 28, 2020

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

创建者 Laurent R

Mar 31, 2019

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

创建者 Himanshu C

Apr 5, 2018

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

创建者 Ian S

Jun 29, 2016

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

创建者 Julio C R N

Jul 16, 2020

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

创建者 Chih-Wei P

Aug 26, 2016

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

创建者 Camila R M

Apr 10, 2021

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

创建者 KSHITIJ S C

Sep 2, 2020

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

创建者 Jingyuan “ Z

May 10, 2019

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

创建者 Gourav B

Jul 4, 2018

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

创建者 John K

Jun 27, 2017

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

创建者 Jeyalakshmi S

May 14, 2016

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

创建者 Martin S R

May 8, 2020

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

创建者 Heather G

Mar 20, 2016

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

创建者 Sushmita G

Mar 2, 2016

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

创建者 Mehmet B

Oct 4, 2020

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

创建者 Sohan A

Mar 10, 2020

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

创建者 Hao X

Jun 7, 2018

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

创建者 Waldemar T

Jun 12, 2017

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