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.
제공자:
이 강좌에 대하여
직원에게 수요가 높은 기술을 교육하면 회사가 이점을 얻을 수 있습니까?
비즈니스를 위한 Coursera 경험해 보기배울 내용
Understand common data storage systems
Apply data cleaning basics to make data "tidy"
Use R for text and date manipulation
Obtain usable data from the web, APIs, and databases
귀하가 습득할 기술
- Data Manipulation
- Regular Expression (REGEX)
- R Programming
- Data Cleansing
직원에게 수요가 높은 기술을 교육하면 회사가 이점을 얻을 수 있습니까?
비즈니스를 위한 Coursera 경험해 보기제공자:
강의 계획표 - 이 강좌에서 배울 내용
Week 1
Week 2
Week 3
Week 4
검토
- 5 stars67.58%
- 4 stars23.61%
- 3 stars5.84%
- 2 stars1.61%
- 1 star1.33%
GETTING AND CLEANING DATA의 최상위 리뷰
This course is amazing! I have spent the majority of my time in R merely doing analytics. This course taught me the tools needed to go out and grab the data that I need for those analytics.
Easy, mostly instructive Course. The Assignments and quizzes are quite good, and illustrates the lessons very well.
See the videos for general presentation, but use the energy on the excersizes.
I found the last project insufficiently explained. I was struggling in understanding what the task is. A bit more clear task description (as in Course 2) would be really appreciated.
This course provides an introduction of some important concepts and tools on a very important aspect of data science: cleaning and organizing data before any analysis. A must for any data scientist.
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