Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data. The course will cover the basics needed for collecting, cleaning, and sharing data.
課程信息
4.6
5,571 個評分
您將學到的內容有
Apply data cleaning basics to make data "tidy"
Obtain usable data from the web, APIs, and databases
Understand common data storage systems
Use R for text and date manipulation
您將獲得的技能
Data ManipulationRegular Expression (REGEX)R ProgrammingData Cleansing
教學大綱 - 您將從這門課程中學到什麼
週
1Week 1
In this first week of the course, we look at finding data and reading different file types.
9 個視頻 （總計 67 分鐘）, 4 個閱讀材料, 1 個測驗
9 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
4 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
1 個練習
Week 1 Quiz10分鐘
週
2Week 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.
5 個視頻 （總計 41 分鐘）, 1 個測驗
5 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
1 個練習
Week 2 Quiz10分鐘
週
3Week 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.
7 個視頻 （總計 60 分鐘）, 1 個閱讀材料, 4 個測驗
7 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
1 個閱讀材料
Practical R Exercises in swirl Part 210分鐘
1 個練習
Week 3 Quiz10分鐘
週
4Week 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.
5 個視頻 （總計 34 分鐘）, 2 個閱讀材料, 3 個測驗
5 個視頻
Regular Expressions I5分鐘
Regular Expressions II8分鐘
Working with Dates6分鐘
Data Resources3分鐘
2 個閱讀材料
Practical R Exercises in swirl Part 410分鐘
Post-Course Survey10分鐘
1 個練習
Week 4 Quiz10分鐘
4.6
882 個審閱40%
完成這些課程後已開始新的職業生涯
35%
通過此課程獲得實實在在的工作福利
熱門審閱
創建者 BE•Oct 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 DH•Feb 2nd 2016
Easy, mostly instructive Course. The Assignments and quizzes are quite good, and illustrates the lessons very well.\n\nSee the videos for general presentation, but use the energy on the excersizes.
講師
Jeff Leek, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Roger D. Peng, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Brian Caffo, PhD
Professor, BiostatisticsBloomberg School of Public Health
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 数据科学 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.
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