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Getting and Cleaning Data(으)로 돌아가기

존스홉킨스대학교의 Getting and Cleaning Data 학습자 리뷰 및 피드백

4.6
6,690개의 평가
1,035개의 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

BE

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.

DH

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.

필터링 기준:

Getting and Cleaning Data의 996개 리뷰 중 201~225

교육 기관: reem z

Jun 23, 2018

A great course and you learn exactly what the title says . I found it fun to work on It

교육 기관: Tine M

Nov 14, 2017

Great course, I've learned a lot about analyzing data sets and creating tidy data sets.

교육 기관: Robert K

May 01, 2017

Fantastic! I find myself using the information I learned in the class on a daily basis.

교육 기관: Boris B

Feb 06, 2016

Great Course if want to know what data really is and how to handle it in the right way.

교육 기관: Alia E

Feb 27, 2017

Wasn't excited about it. But I've used and re-used the materials for work. Good stuff.

교육 기관: Tseliso I M

Feb 02, 2017

Of the courses I have done so far in the specialization, this was the most practical.

교육 기관: Tacao M

Feb 03, 2016

Very interesting material and basic knowledge on R to read files and produce tidy data

교육 기관: Tomas A M

Aug 22, 2017

Excellent course mates! Lots & lots of very useful info & examples! Thanks so much!!!

교육 기관: Dmytro I

May 15, 2017

It's a great course, however, explanations to the final assignment were rather vague.

교육 기관: Sambit C

Oct 12, 2016

A great course. Learned a lot. However student has to put an extra effort practicing.

교육 기관: Ksenia K

May 03, 2016

Great course, more difficult than previous two, but also more challenging and useful!

교육 기관: Wang J

May 02, 2016

Great practice for R programming and the MySQL part is extremely helpful for my work.

교육 기관: Leonardo A

Aug 08, 2019

This is the best course so far. Very challenging project at the end. I learned a lot

교육 기관: Jorge A B J

Jul 25, 2019

Very nice course! Would defensively recommend to anyone seeking this specialization!

교육 기관: Puja G

Feb 07, 2018

Very useful to get hands on experience in data science to solve real world problems!

교육 기관: Abay J

Jan 21, 2019

Love quizzes and a course project. Working on them develops you as a data scientist

교육 기관: Ajendra S

Aug 29, 2018

I really liked this course. This course helped me to understand the data wrangling.

교육 기관: Tiago P F

Jan 03, 2018

Excellent course, with a very important focus on documentation and code versioning.

교육 기관: jutzhang

Jun 27, 2016

建议更新课程中所涉及函数的使用方法

Please update the using methods of some functions in this lecture.

교육 기관: Andaru

Feb 13, 2016

90% of data science is cleaning, this really gets people accepting that key concept

교육 기관: Vitalii S

Jul 20, 2017

This course gave me an insights regarding data cleaning. Very grateful, thank you!

교육 기관: Karthic C

Jul 18, 2017

Well put together course. Happy and eager to finish the rest of the specialization

교육 기관: Thor R

Jan 18, 2019

Useful, the course is as much an introduction to R- part 2 as about cleaning data

교육 기관: Raunak S

Oct 05, 2018

excellent course to get started with to learn the basic concepts of data tidying.

교육 기관: Sunder R V

Aug 28, 2017

Enjoyed the course and learnt quite a few things in my quest for "Data Analytics"