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
提供方
課程信息
對員工進行熱門技能培訓能否為您的公司帶來益處？
體驗 Coursera 企業版您將獲得的技能
- Data Manipulation
- Regular Expression (REGEX)
- R Programming
- Rstudio
對員工進行熱門技能培訓能否為您的公司帶來益處？
體驗 Coursera 企業版
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.
授課大綱 - 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
- 5 stars59.47%
- 4 stars25.06%
- 3 stars7.51%
- 2 stars3.23%
- 1 star4.71%
來自THE R PROGRAMMING ENVIRONMENT的熱門評論
Good Practice..........!!!...really helpful for building data science concept through R Programming.........Really salute for hardworking of instructor..................!!!
The whole course was easy to follow except for the last questions of the last exam where the merged data set results into a null data frame after filtering.
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.
Great Introduction, may we worth clarifying that for Data Manipulation the script must be saved before entering submit() as you cannot make progress.
關於 Mastering Software Development in R 專項課程
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.
常見問題
我什么时候能够访问课程视频和作业？
我订阅此专项课程后会得到什么？
有助学金吗？
還有其他問題嗎？請訪問 學生幫助中心。
