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Getting and Cleaning Data(으)로 돌아가기

존스홉킨스대학교의 Getting and Cleaning Data 학습자 리뷰 및 피드백

4.5
별점
7,940개의 평가

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

2020년 5월 2일

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.

BE

2016년 10월 25일

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 1,278개 리뷰 중 126~150

교육 기관: Sudhin B

2018년 3월 17일

So knowledgeable and interesting course. I have learned much about data cleaning and getting from different sources. Finally thanks to coursera team for giving us the opportunity.

교육 기관: Charles K

2016년 2월 6일

This is a very well put together course. It teaches the basics of data cleansing and how to setup data for modeling--by far the most foundational technical aspect of data analysis.

교육 기관: John B

2018년 9월 22일

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: Eugene K

2018년 1월 7일

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

2018년 6월 16일

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

2017년 10월 17일

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

2020년 5월 23일

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

2016년 2월 1일

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

2019년 1월 8일

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

2017년 8월 26일

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

2017년 2월 2일

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

2018년 7월 22일

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

2020년 7월 29일

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: Muhammad J K

2022년 2월 17일

I have enjoyed the course and course leaning, teching methode was very very nice. I got success and I am very happy.

Thanks for study help (Coursera Study plateform).

교육 기관: Sreemoyee M

2020년 1월 15일

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

2019년 8월 6일

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

2017년 11월 7일

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

2017년 5월 28일

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

2017년 3월 5일

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

2017년 1월 25일

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

2017년 10월 24일

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

2019년 2월 13일

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

2018년 11월 8일

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

2016년 12월 5일

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

2017년 12월 24일

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.