课程信息
30,028 次近期查看

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

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中级

完成时间大约为16 小时

建议:10 hours/week...

英语(English)

字幕:英语(English)

您将获得的技能

Data ManipulationRegular Expression (REGEX)R ProgrammingRstudio

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为16 小时

建议:10 hours/week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 2 小时

Basic R Language

1 个视频 (总计 2 分钟), 27 个阅读材料
27 个阅读材料
Course Textbook: Mastering Software Development in R1分钟
Syllabus10分钟
Swirl Assignments10分钟
Datasets10分钟
Lesson Introduction2分钟
Evaluation3分钟
Objects1分钟
Numbers1分钟
Creating Vectors1分钟
Mixing Objects1分钟
Explicit Coercion3分钟
Matrices3分钟
Lists2分钟
Factors4分钟
Missing Values3分钟
Data Frames3分钟
Names4分钟
Attributes1分钟
Summary1分钟
The Importance of Tidy Data5分钟
The “Tidyverse”4分钟
Reading Tabular Data with the readr Package10分钟
Reading Web-Based Data1分钟
Flat files online10分钟
Requesting data through a web API10分钟
Scraping web data2分钟
Parsing JSON, XML, or HTML data3分钟
完成时间为 6 小时

Basic R Language: Lesson Choices

2 个测验
1 个练习
Swirl Lessons3小时
2
完成时间为 1 小时

Data Manipulation

11 个阅读材料
11 个阅读材料
Basic Data Manipulation10分钟
Piping7分钟
Summarizing data10分钟
Selecting and filtering data10分钟
Adding, changing, or renaming columns7分钟
Spreading and gathering data10分钟
Merging datasets10分钟
Working with Dates, Times, Time Zones3分钟
Converting to a date or date-time class7分钟
Pulling out date and time elements5分钟
Working with time zones8分钟
完成时间为 6 小时

Data Manipulation: Lesson Choices

2 个测验
1 个练习
Swirl Lessons3小时
3
完成时间为 1 小时

Text Processing, Regular Expression, & Physical Memory

9 个阅读材料
9 个阅读材料
Text Processing and Regular Expressions1分钟
Text Manipulation Functions in R10分钟
Regular Expressions15分钟
RegEx Functions in R5分钟
The stringr Package10分钟
Summary1分钟
The Role of Physical Memory10分钟
Back of the Envelope Calculations8分钟
Internal Memory Management in R5分钟
完成时间为 6 小时

Text Processing, Regular Expression, & Physical Memory: Lesson Choices

2 个测验
1 个练习
Swirl Lessons3小时
4
完成时间为 5 小时

Large Datasets

7 个阅读材料, 1 个测验
7 个阅读材料
Working with Large Datasets2分钟
In-memory strategies10分钟
Out-of-memory strategies10分钟
Diagnosing Problems5分钟
How to Google Your Way Out of a Jam5分钟
Asking for Help5分钟
Quiz Instructions4小时
1 个练习
Reading and Summarizing Data20分钟
4.4
232 个审阅Chevron Right

46%

完成这些课程后已开始新的职业生涯

42%

通过此课程获得实实在在的工作福利

13%

加薪或升职

来自The R Programming Environment的热门评论

创建者 MVDec 26th 2018

Very Very Rigorous Course for a beginner on R language and because of its nature, after completing just one course, I feel like I have gained a lot of knowledge and also familiarity with R language.

创建者 KVJun 18th 2019

A very good course to read and get the valuable content of R language. This is for the students who want to learn and practice the basic and some intermediate concepts of data manipulation.

讲师

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Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Brooke Anderson

Assistant Professor, Environmental & Radiological Health Sciences
Colorado State University

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....

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. This Specialization will give you rigorous training in the R language, including the skills for handling complex data, building R packages, and developing custom data visualizations. You’ll be introduced to indispensable R libraries for data manipulation, like tidyverse, and data visualization and graphics, like ggplot2. You’ll learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers. This Specialization is designed to serve both data analysts, who may want to gain more familiarity with hands-on, fundamental software skills for their everyday work, as well as data mining experts and data scientists, who may want to use R to scale their developing and programming skills, and further their careers as data science experts....
Mastering Software Development in R

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