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Getting and Cleaning Data(으)로 돌아가기

존스홉킨스대학교의 Getting and Cleaning Data 학습자 리뷰 및 피드백

6,511개의 평가
1,009개의 리뷰

강좌 소개

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....

최상위 리뷰


Feb 02, 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.


Oct 26, 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.

필터링 기준:

Getting and Cleaning Data의 969개 리뷰 중 176~200

교육 기관: Cathryn S

Jan 02, 2017

A good course, which helped me understand how to get data off the web and from other sources, and improved my R skills

교육 기관: Hatem K

Dec 05, 2016

Excellent course. You will learn about concepts of 'clean' or tidy data and apply it in R. One of the most important, yet often ignored, aspects of data science.

교육 기관: Abhimanyu B

Jan 03, 2017

Teaches a crucial and often overlooking step in the data analysis workflow. Brilliant tips and insights!

교육 기관: Stepas L

Dec 19, 2016

Loved this course,best so far from all data science .

교육 기관: Rodney A J

Jun 06, 2017

This is a terrific course on obtaining data from various sources and then cleaning the raw data obtained to form useful tidy data sets. The course material learned is reinforced using a very interesting peer-reviewed project based on accelerometer and gyroscopic data from collected from typical human activity.

교육 기관: Shuo C

Feb 21, 2018

This whole specialization is very informative! Highly recommend!

교육 기관: Joaquim M J

Jun 17, 2017


교육 기관: Ricardo M S

Jul 03, 2016

Awesome material and lots to learn

교육 기관: Peter

Mar 23, 2016

Very good class for a beginner. Helps become more comfortable with R programming and aspects of getting data into R

교육 기관: GAURAV S

Aug 01, 2016

Nice course

교육 기관: VIVEK R

Jun 05, 2016

Its really help me a lot to build up my basic concept and now data wrangling is quit bit easy for me.

Thanks :)

교육 기관: Roberto D

Jun 21, 2017

Very useful for deciding best methods pulling data and consistently massage data.

교육 기관: Shaikh M I

Nov 22, 2016

This course is really helpful and very practical. Provides industry standard information and adheres to the scientific principles.

교육 기관: Jiawen C

May 04, 2016

Great course!

교육 기관: Sabyasachi M

Jan 31, 2017

Great teaching method :)

교육 기관: Carlos R

Jul 22, 2017

Good hand on course to learn manipulating data. Thanks!

교육 기관: Randal N

Jan 23, 2018

Very enlightening course. It is the first course where I felt like I was actually doing something data sciency. Would recommend even as a stand alone course because I have now come to appreciate the importance of tidy data in performing successful analyses.

교육 기관: Marina Z

Jul 26, 2017

just a great course

교육 기관: Huang J

Sep 19, 2016

Useful to get the basics right

교육 기관: Prohnițchi V

Oct 02, 2017

Great course. Have learned a lot and discovered powerful tools and approaches.

교육 기관: Boizette

Jul 04, 2017

très complet

교육 기관: Jun Z

Jun 21, 2016

Have challenges, but very useful!

교육 기관: Dimitrios G

Mar 03, 2017

Challenging and very educational. Needs a better explanation on the final peer assignment. Otherwise a great overall experience!

교육 기관: Haoxiang Z

Nov 04, 2017

Learned a lot

교육 기관: Kwun H N

Dec 25, 2017

It is an excellent exercise to work on data cleaning and pre-processing. Also give me the great chance to read through the paper by Hadley Wickham on Tidy Data.