課程信息
4.6
5,356 個評分
859 個審閱
專項課程

第 3 門課程(共 10 門),位於

100% 在線

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

可靈活調整截止日期

根據您的日程表重置截止日期。
完成時間(小時)

完成時間大約為14 小時

建議:5 hours/week...
可選語言

英語(English)

字幕:英語(English), 法語(French), 中文(簡體), 越南語, 俄語(Russian)...

您將學到的內容有

  • Check

    Apply data cleaning basics to make data "tidy"

  • Check

    Obtain usable data from the web, APIs, and databases

  • Check

    Understand common data storage systems

  • Check

    Use R for text and date manipulation

您將獲得的技能

Data ManipulationRegular Expression (REGEX)R ProgrammingData Cleansing
專項課程

第 3 門課程(共 10 門),位於

100% 在線

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

可靈活調整截止日期

根據您的日程表重置截止日期。
完成時間(小時)

完成時間大約為14 小時

建議:5 hours/week...
可選語言

英語(English)

字幕:英語(English), 法語(French), 中文(簡體), 越南語, 俄語(Russian)...

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 2 小時

Week 1

In this first week of the course, we look at finding data and reading different file types....
Reading
9 個視頻(共 67 分鐘), 4 個閱讀材料, 1 個測驗
Video9 個視頻
Raw and Processed Data7分鐘
Components of Tidy Data9分鐘
Downloading Files7分鐘
Reading Local Files4分鐘
Reading Excel Files3分鐘
Reading XML12分鐘
Reading JSON5分鐘
The data.table Package11分鐘
Reading4 個閱讀材料
Welcome to Week 110分鐘
Syllabus10分鐘
Pre-Course Survey10分鐘
Practical R Exercises in swirl Part 110分鐘
Quiz1 個練習
Week 1 Quiz10分鐘
2
完成時間(小時)
完成時間為 1 小時

Week 2

Welcome to Week 2 of Getting and Cleaning Data! The primary goal is to introduce you to the most common data storage systems and the appropriate tools to extract data from web or from databases like MySQL. ...
Reading
5 個視頻(共 41 分鐘), 1 個測驗
Video5 個視頻
Reading from HDF56分鐘
Reading from The Web6分鐘
Reading From APIs7分鐘
Reading From Other Sources4分鐘
Quiz1 個練習
Week 2 Quiz10分鐘
3
完成時間(小時)
完成時間為 10 小時

Week 3

Welcome to Week 3 of Getting and Cleaning Data! This week the lectures will focus on organizing, merging and managing the data you have collected using the lectures from Weeks 1 and 2. ...
Reading
7 個視頻(共 60 分鐘), 1 個閱讀材料, 4 個測驗
Video7 個視頻
Summarizing Data11分鐘
Creating New Variables10分鐘
Reshaping Data9分鐘
Managing Data Frames with dplyr - Introduction3分鐘
Managing Data Frames with dplyr - Basic Tools12分鐘
Merging Data6分鐘
Reading1 個閱讀材料
Practical R Exercises in swirl Part 210分鐘
Quiz1 個練習
Week 3 Quiz10分鐘
4
完成時間(小時)
完成時間為 6 小時

Week 4

Welcome to Week 4 of Getting and Cleaning Data! This week we finish up with lectures on text and date manipulation in R. In this final week we will also focus on peer grading of Course Projects. ...
Reading
5 個視頻(共 34 分鐘), 2 個閱讀材料, 3 個測驗
Video5 個視頻
Regular Expressions I5分鐘
Regular Expressions II8分鐘
Working with Dates6分鐘
Data Resources3分鐘
Reading2 個閱讀材料
Practical R Exercises in swirl Part 410分鐘
Post-Course Survey10分鐘
Quiz1 個練習
Week 4 Quiz10分鐘
4.6
職業方向

40%

完成這些課程後已開始新的職業生涯
工作福利

83%

通過此課程獲得實實在在的工作福利

熱門審閱

創建者 BEOct 26th 2016

This course is really a challenging and compulsory for any one who wants to be a data scientist or working in any sort of data. It teaches you how to make very palatable data-set fro ma messy data.

創建者 ARMay 14th 2018

Loved the structure of the course. Learned a lot. The course project seemed a little funky , especially creating the codebook for an already existing set of data but was a useful teaching aid.

講師

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Jeff Leek, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

關於 Johns Hopkins University

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 Data Science 專項課程

Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material....
Data Science

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