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.
本課程是 Mastering Software Development in R 專項課程 專項課程的一部分
The R Programming Environment
提供方
課程信息
學生職業成果
46%
42%
13%
您將獲得的技能
學生職業成果
46%
42%
13%
可分享的證書
100% 在線
第 1 門課程（共 5 門）
可靈活調整截止日期
中級
完成時間大約為18 小時
英語（English）
提供方
约翰霍普金斯大学
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
教學大綱 - 您將從這門課程中學到什麼
Basic R Language
In this module, you'll learn the basics of R, including syntax, some tidy data principles and processes, and how to read data into R.
Basic R Language: Lesson Choices
Data Manipulation
During this module, you'll learn to summarize, filter, merge, and otherwise manipulate data in R, including working through the challenges of dates and times.
Data Manipulation: Lesson Choices
Text Processing, Regular Expression, & Physical Memory
During this module, you'll learn to use R tools and packages to deal with text and regular expressions. You'll also learn how to manage and get the most from your computer's physical memory when working in R.
Text Processing, Regular Expression, & Physical Memory: Lesson Choices
Choice 1: Get credit while using swirl | Choice 2: Get credit by providing a code from swirl
Large Datasets
In this final module, you'll learn how to overcome the challenges of working with large datasets both in memory and out as well as how to diagnose problems and find help.
審閱
4.4
來自THE R PROGRAMMING ENVIRONMENT的熱門評論
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.
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.
Good to learn the possibilities in the R environment. In the end you learn most by applying it to your own projects (with a lot of help in available documentation or via internet sea).
Excellent class. I had already done a lot of the swirls and would have liked that to be in my record somewhere, although it really wasn't hard--and was probably good--to repeat them.
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.
Very good starting course, covers all the basics.\n\nMy 2 cents: I would prefer more tests like the last one than the swirl lessons, they're more challenging thus you learn more.
Good Practice..........!!!...really helpful for building data science concept through R Programming.........Really salute for hardworking of instructor..................!!!
First three weeks materials are amazing, and I like to interactive with swirl(). If there are some more videos rather than reading materials, it would be interesting.
The R Programing Environment is very supportive environment, and I appriciate the guideline and the materials. futhermore, the course was good begining. Thanks
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
This course gave a great review of R. It also did a great job of highlighting the power of the tidyverse library for preparing data for analysis.
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.
關於 Mastering Software Development in R 專項課程
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