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.
R 语言程序设计（中文版）
提供方
约翰霍普金斯大学
课程信息
644,298 次近期查看
Learner Career Outcomes
36%
完成这些课程后已开始新的职业生涯
35%
通过此课程获得实实在在的工作福利
11%
加薪或升职
您将学到的内容有
Collect detailed information using R profiler
Configure statistical programming software
Make use of R loop functions and debugging tools
Understand critical programming language concepts
您将获得的技能
Data AnalysisDebuggingR ProgrammingRstudio
Learner Career Outcomes
36%
完成这些课程后已开始新的职业生涯
35%
通过此课程获得实实在在的工作福利
11%
加薪或升职
100% 在线
立即开始，按照自己的计划学习。
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中级
You should have beginner level experience in Python. Familarity with regression is recommended.
完成时间大约为20 小时
英语（English）
字幕：阿拉伯语（Arabic）, 法语（French）, 中文（简体）, 巴西葡萄牙语, 越南语, 英语（English）, 西班牙语（Spanish）, 日语
教学大纲 - 您将从这门课程中学到什么
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.
完成时间为 25 小时
28 个视频 （总计 129 分钟）, 9 个阅读材料, 8 个测验
28 个视频
Installing R on Windows3分钟
Installing R Studio (Mac)1分钟
Writing Code / Setting Your Working Directory (Windows)7分钟
Writing Code / Setting Your Working Directory (Mac)7分钟
Introduction1分钟
Overview and History of R16分钟
Getting Help13分钟
R Console Input and Evaluation4分钟
Data Types - R Objects and Attributes4分钟
Data Types - Vectors and Lists6分钟
Data Types - Matrices3分钟
Data Types - Factors4分钟
Data Types - Missing Values2分钟
Data Types - Data Frames2分钟
Data Types - Names Attribute1分钟
Data Types - Summary43
Reading Tabular Data5分钟
Reading Large Tables7分钟
Textual Data Formats4分钟
Connections: Interfaces to the Outside World4分钟
Subsetting - Basics4分钟
Subsetting - Lists4分钟
Subsetting - Matrices2分钟
Subsetting - Partial Matching1分钟
Subsetting - Removing Missing Values3分钟
Vectorized Operations3分钟
Introduction to swirl1分钟
9 个阅读材料
Welcome to R Programming10分钟
About the Instructor10分钟
Pre-Course Survey10分钟
Syllabus10分钟
Course Textbook10分钟
Course Supplement: The Art of Data Science10分钟
Data Science Podcast: Not So Standard Deviations10分钟
Getting Started and R Nuts and Bolts10分钟
Practical R Exercises in swirl Part 110分钟
1 个练习
Week 1 Quiz40分钟
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.
完成时间为 12 小时
13 个视频 （总计 91 分钟）, 3 个阅读材料, 5 个测验
13 个视频
Control Structures - If-else1分钟
Control Structures - For loops4分钟
Control Structures - While loops3分钟
Control Structures - Repeat, Next, Break4分钟
Your First R Function10分钟
Functions (part 1)9分钟
Functions (part 2)7分钟
Scoping Rules - Symbol Binding10分钟
Scoping Rules - R Scoping Rules8分钟
Scoping Rules - Optimization Example (OPTIONAL)9分钟
Coding Standards8分钟
Dates and Times10分钟
3 个阅读材料
Week 2: Programming with R10分钟
Practical R Exercises in swirl Part 210分钟
Programming Assignment 1 INSTRUCTIONS: Air Pollution10分钟
2 个练习
Week 2 Quiz20分钟
Programming Assignment 1: Quiz20分钟
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.
完成时间为 10 小时
8 个视频 （总计 61 分钟）, 2 个阅读材料, 4 个测验
8 个视频
Loop Functions - apply7分钟
Loop Functions - mapply4分钟
Loop Functions - tapply3分钟
Loop Functions - split9分钟
Debugging Tools - Diagnosing the Problem12分钟
Debugging Tools - Basic Tools6分钟
Debugging Tools - Using the Tools8分钟
2 个阅读材料
Week 3: Loop Functions and Debugging10分钟
Practical R Exercises in swirl Part 310分钟
1 个练习
Week 3 Quiz10分钟
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.
完成时间为 11 小时
6 个视频 （总计 42 分钟）, 4 个阅读材料, 5 个测验
6 个视频
Simulation - Generating Random Numbers7分钟
Simulation - Simulating a Linear Model4分钟
Simulation - Random Sampling2分钟
R Profiler (part 1)10分钟
R Profiler (part 2)10分钟
4 个阅读材料
Week 4: Simulation & Profiling10分钟
Practical R Exercises in swirl Part 410分钟
Programming Assignment 3 INSTRUCTIONS: Hospital Quality10分钟
Post-Course Survey10分钟
2 个练习
Week 4 Quiz20分钟
Programming Assignment 3: Quiz20分钟
4.6
3,265 条评论来自R 语言程序设计（中文版）的热门评论
"R Programming" forces you to dive in deep.\n\nThese skills serve as a strong basis for the rest of the data science specialization.\n\nMaterial is in depth, but presented clearly. Highly recommended!
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.
关于 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.
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