課程信息
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中級

完成時間大約為16 小時

建議:10 hours/week...

英語(English)

字幕:英語(English)

您將獲得的技能

Data ManipulationRegular Expression (REGEX)R ProgrammingRstudio

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為16 小時

建議:10 hours/week...

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 2 小時

Basic R Language

1 個視頻 (總計 2 分鐘), 27 個閱讀材料
27 個閱讀材料
Course Textbook: Mastering Software Development in R1分鐘
Syllabus10分鐘
Swirl Assignments10分鐘
Datasets10分鐘
Lesson Introduction2分鐘
Evaluation3分鐘
Objects1分鐘
Numbers1分鐘
Creating Vectors1分鐘
Mixing Objects1分鐘
Explicit Coercion3分鐘
Matrices3分鐘
Lists2分鐘
Factors4分鐘
Missing Values3分鐘
Data Frames3分鐘
Names4分鐘
Attributes1分鐘
Summary1分鐘
The Importance of Tidy Data5分鐘
The “Tidyverse”4分鐘
Reading Tabular Data with the readr Package10分鐘
Reading Web-Based Data1分鐘
Flat files online10分鐘
Requesting data through a web API10分鐘
Scraping web data2分鐘
Parsing JSON, XML, or HTML data3分鐘
完成時間為 6 小時

Basic R Language: Lesson Choices

2 個測驗
1 個練習
Swirl Lessons3小時
2
完成時間為 1 小時

Data Manipulation

11 個閱讀材料
11 個閱讀材料
Basic Data Manipulation10分鐘
Piping7分鐘
Summarizing data10分鐘
Selecting and filtering data10分鐘
Adding, changing, or renaming columns7分鐘
Spreading and gathering data10分鐘
Merging datasets10分鐘
Working with Dates, Times, Time Zones3分鐘
Converting to a date or date-time class7分鐘
Pulling out date and time elements5分鐘
Working with time zones8分鐘
完成時間為 6 小時

Data Manipulation: Lesson Choices

2 個測驗
1 個練習
Swirl Lessons3小時
3
完成時間為 1 小時

Text Processing, Regular Expression, & Physical Memory

9 個閱讀材料
9 個閱讀材料
Text Processing and Regular Expressions1分鐘
Text Manipulation Functions in R10分鐘
Regular Expressions15分鐘
RegEx Functions in R5分鐘
The stringr Package10分鐘
Summary1分鐘
The Role of Physical Memory10分鐘
Back of the Envelope Calculations8分鐘
Internal Memory Management in R5分鐘
完成時間為 6 小時

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

2 個測驗
1 個練習
Swirl Lessons3小時
4
完成時間為 5 小時

Large Datasets

7 個閱讀材料, 1 個測驗
7 個閱讀材料
Working with Large Datasets2分鐘
In-memory strategies10分鐘
Out-of-memory strategies10分鐘
Diagnosing Problems5分鐘
How to Google Your Way Out of a Jam5分鐘
Asking for Help5分鐘
Quiz Instructions4小時
1 個練習
Reading and Summarizing Data20分鐘
4.4
225 個審閱Chevron Right

44%

完成這些課程後已開始新的職業生涯

41%

通過此課程獲得實實在在的工作福利

14%

加薪或升職

來自The R Programming Environment的熱門評論

創建者 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.

創建者 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.

講師

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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

關於 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....

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. 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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