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Getting and Cleaning Data(으)로 돌아가기

존스홉킨스대학교의 Getting and Cleaning Data 학습자 리뷰 및 피드백

6,560개의 평가
1,012개의 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


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.


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 972개 리뷰 중 51~75

교육 기관: Scott D

Dec 30, 2018

This course is great. The tactical skills in R you really need on the job.

교육 기관: Silas S

Nov 14, 2018

Fantastic course. Highly recommended

교육 기관: Koen V

Nov 15, 2018

Fun course!

교육 기관: Ji H W

Jul 31, 2018

Great lecture and help understanding concepts throughout the lecture

교육 기관: Bora A

Jul 31, 2018

Thanks for the excellent course

교육 기관: Yash G

Aug 07, 2018

It was really an enriching course. I learnt a lot about the raw data formats and tools and techniques to get the best out of that raw data. Highly recommended

교육 기관: Sebastian O V

Aug 06, 2018

Great course teaches intermediate and andvanced skills to manipullate and clean data. Begginers should make an extra effort

교육 기관: Anand

Aug 14, 2018

Good course and pace

교육 기관: Satish V

Jul 22, 2018

This course was very useful, informative and interesting. However, I did feel that the course assignment seems to be, perhaps purposefully, but a bit unnecessarily vague.

교육 기관: César H G S

Sep 02, 2018

Good course!

교육 기관: David R

Sep 03, 2018

Great course covering a wide range of data types likely to be encountered in the field of data science. Well explained.

교육 기관: Ganesh R

Sep 05, 2018

Nice Course.


Sep 05, 2018

lovein' it!

교육 기관: Savitri

Aug 26, 2018

its the best course for the data science students and it will help all the student who are going to join or who want to start their career in data science.

교육 기관: Sangdon C

Oct 12, 2018


교육 기관: Royce S

Oct 11, 2018

Very useful content and challenging assignments

교육 기관: Bojan B

Oct 14, 2018

Great course with great materials. Easy to understand and to learn.

교육 기관: Chetan T

Oct 19, 2018

The journey through the entire course was quite exceptional for me. It was great to hone the skills of programming and especially in this digital world where data is key for every analysis, inference, prediction and what not! When everyone looks at neat and tidy data that one can rely on, it is extremely important to understand and know the finer nuances of what it takes to get a nice and efficient dataset and that is the essence of this course.

교육 기관: Shashwat K

Aug 18, 2018

good course.

교육 기관: Anup K M

Sep 15, 2018


교육 기관: John A R B

Sep 22, 2018

How to get a clean the data is a very important knowledge for the future data scientist and data analyst. For me this course was very important I very recommend take this course.

교육 기관: Mohd I S B M Z

Sep 23, 2018

Great project course challenge

교육 기관: Georgios P

Sep 24, 2018

The most crucial part of statistical inference or machine learning is tidy data and this course provides the basic tidy data rules!

교육 기관: Сетдеков К Р

Sep 27, 2018

Helped a lot form my understanding of a good workflow for data collection and processing.

교육 기관: Premkumar S

Sep 28, 2018

Excellent course with some great exercises put together that are very practical.