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Getting and Cleaning Data(으)로 돌아가기

존스홉킨스대학교의 Getting and Cleaning Data 학습자 리뷰 및 피드백

4.6
별점
7,300개의 평가
1,167개의 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

HS

May 03, 2020

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.

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 1,129개 리뷰 중 101~125

교육 기관: Eugene K

Jan 08, 2018

Great course on tidy data. Very useful in understanding how to use different types of data (csv, XML, API) and how to manipulate the data so that you can perform analyses on it.

교육 기관: Mohammad A

Jun 16, 2018

Excellent course, and quizzes and lecture were very teaching. But some materials needs to be updated up to date , like subsetting columns in data.table the slides were absolute.

교육 기관: João F

Oct 17, 2017

Great ready-to-use skills for common tasks of a Data Scientist. Lays the foundations for further self-development in the topics taught. Heavy on R. Very challenging assignments.

교육 기관: Amsalu B B

May 23, 2020

This specific course is good but when it comes to the assignments, it's more confused than the course work and the description of the assignment is unclear too, at least to me.

교육 기관: Jonathan D B

Feb 01, 2016

really thorough class... come prepared to learn and be patient as your going to get your hands pretty dirty reading data, cleaning it and manipulating the result sets with R

교육 기관: Luis E B P

Jan 08, 2019

I think this course is really good, the instructors give you a lot of tools to handle data bases! I would recomend this course to any person that wants to learn about this.

교육 기관: Joyce

Aug 26, 2017

Super useful, there are so many raw data in the practical world, which are needed to be cleaned, so that the analysts and other people can easily get information from data.

교육 기관: Christopher R

Feb 02, 2017

I use so much of what I've learned here on a day to day basis! Using the suite of functions from ggplot, dplyr, plyr and others has greatly reduced my data management time.

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: Anand R

Jul 29, 2020

Course was very useful and learnt about how to handle the data especially raw data and also fetching them with various aspects. Thanks Jeff and team and also coursera

교육 기관: Sreemoyee M

Jan 15, 2020

The challenging quizzes and assignments are a main reason why this course is so great! This course truly ensures that you truly understand and implement the videos.

교육 기관: Jorge B S

Aug 06, 2019

I have found this course very useful to gain a nice overview of the main tools to obtain and clean data. Moreover, for me it was challenging, which is always a plus.

교육 기관: Diego T B

Nov 07, 2017

Very interesting. Global view to process Data and try to explain with very useful techniques the processing or cleaning data with regular expressions. I enjoyed it!

교육 기관: Johann R

May 28, 2017

A great course in which many important concepts and techniques are covered. It also covers many handy tools/libraries that one can use to clean and manipulate data.

교육 기관: Mauro S d S

Mar 05, 2017

Very intense and covering a lot of material - After about an year from having the course and with a different understanding, this is probably the course to revisit.

교육 기관: John J O G

Jan 25, 2017

Muy buen curso y con buena evaluación de los temas mediante asignaciones varias con estudios en el mundo real que lo preparan para estar analizando trabajos reales

교육 기관: Dany M

Oct 24, 2017

Great course! I loved it. It's just informal enough and rigorous enough. The pace is enjoyable and the experience of the instructor carries well.

Highly recommend.

교육 기관: Nimalka W

Feb 13, 2019

Useful general course on tidying data and learning to import into R from various sources. Doesn't get into sequencing data import, but looks at other common ones

교육 기관: Ayas S

Nov 08, 2018

This course was very intense and not easy but over all, after doing all the work! Oh man I feel I have way more confidence in my R skills and Data understanding.

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: 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.

교육 기관: Y S K

Apr 23, 2017

This course gives an excellent introduction to the various data collection and tidying processes using R. This course is a must for any aspiring data scientist.

교육 기관: Jihad R

Nov 04, 2016

Great course! Very well structured and complete in the knowledge it brings both on the R language itself and in the concept of data clean up and transformation.

교육 기관: Stefan L

Mar 14, 2016

Interesting course with a lot of time intensive quizes. It, however, opened my eyes on how to effectively work towards clean data.

Thanks for the great courses!

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