你将学到什么
Collect detailed information using R profiler
Configure statistical programming software
Make use of R loop functions and debugging tools
Understand critical programming language concepts
课程概况
主要研究如何利用R语言进行编程和有效的数据分析，这是约翰-霍普金斯大学数据科学专业化课程的第二套课程。
大家将学习如何安装设置统计编程环境所需要的电脑软件，讨论在高水平统计语言中实现泛型编程语言的相关概念。课程涵盖统计计算中的一些实际问题，其中包括R语言编程，R语言读取数据，加载R语言程序包，编写R语言函数，调试以及R语言代码的组织与注释。针对统计数据分析和优化的内容，我们会提供实操示例。
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.
课程大纲
周1
完成时间为 25 小时
Week 1: Background, Getting Started, and Nuts & Bolts
This week covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data. I recommend that you watch the videos in the listed order, but watching the videos out of order isn't going to ruin the story.
28 个视频 （总计 129 分钟）, 9 个阅读材料, 8 个测验
周2
完成时间为 12 小时
Week 2: Programming with R
Welcome to Week 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions.
We also introduce the first programming assignment for the course, which is due at the end of the week.
13 个视频 （总计 91 分钟）, 3 个阅读材料, 5 个测验
周3
完成时间为 10 小时
Week 3: Loop Functions and Debugging
We have now entered the third week of R Programming, which also marks the halfway point. The lectures this week cover loop functions and the debugging tools in R. These aspects of R make R useful for both interactive work and writing longer code, and so they are commonly used in practice.
8 个视频 （总计 61 分钟）, 2 个阅读材料, 4 个测验
周4
完成时间为 11 小时
Week 4: Simulation & Profiling
This week covers how to simulate data in R, which serves as the basis for doing simulation studies. We also cover the profiler in R which lets you collect detailed information on how your R functions are running and to identify bottlenecks that can be addressed. The profiler is a key tool in helping you optimize your programs. Finally, we cover the str function, which I personally believe is the most useful function in R.
