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.
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课程信息
Familiarity with regression is recommended.
对员工进行热门技能培训能否为您的公司带来益处?
体验 Coursera 企业版您将学到的内容有
Understand critical programming language concepts
Configure statistical programming software
Make use of R loop functions and debugging tools
Collect detailed information using R profiler
您将获得的技能
- Data Analysis
- Debugging
- R Programming
- Rstudio
Familiarity with regression is recommended.
对员工进行热门技能培训能否为您的公司带来益处?
体验 Coursera 企业版提供方
授课大纲 - 您将从这门课程中学到什么
Week 1: Background, Getting Started, and Nuts & Bolts
Week 2: Programming with R
Week 3: Loop Functions and Debugging
Week 4: Simulation & Profiling
审阅
- 5 stars68.10%
- 4 stars22.15%
- 3 stars5.83%
- 2 stars2.06%
- 1 star1.82%
来自R 语言程序设计(中文版)的热门评论
I would have preferred the 'robot voice' concept from the toolbox course, since it could be updated to more recent R upgrades, but the assignments really made me think and that was my favorite part.
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.
Very challenging, but good course. I've been programming in R for over a year, but there were still some things for me to pick up in this class. Assignments were a challenge, but satisfying to tackle.
I am pleasantly surprised with the quality of this course. For a beginner, the Swirl exercises are incredibly helpful and I was able to build confidence in working with R because of them. Thank you!
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