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.
本课程是 Mastering Software Development in R 专项课程 专项课程的一部分
提供方
课程信息
您将获得的技能
- Data Manipulation
- Regular Expression (REGEX)
- R Programming
- Rstudio
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.
授课大纲 - 您将从这门课程中学到什么
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.
审阅
- 5 stars59.58%
- 4 stars25.02%
- 3 stars7.52%
- 2 stars3.23%
- 1 star4.63%
来自THE R PROGRAMMING ENVIRONMENT的热门评论
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
A thorough course that covers a lot of efficient data manipulation styles within the R environment. I learned a lot of neat tricks that help with quick analysis of large data frames.
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.
关于 Mastering Software Development in R 专项课程
R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians. This Specialization covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing and scaling useful data science results and products.
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