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Getting and Cleaning Data(으)로 돌아가기

존스홉킨스대학교의 Getting and Cleaning Data 학습자 리뷰 및 피드백

4.6
별점
7,600개의 평가
1,227개의 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
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.

DH
2016년 2월 1일

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 1,187개 리뷰 중 51~75

교육 기관: Debayan D

2017년 7월 25일

The Course Project was daunting at first, but I reviewed my notes over and over again, tried reading from the site where the raw data was made available and constructed images of how the TIDY data should look like. This is a very important course in this specialization. The course has given me an abstract sense of what to expect and what to do while cleaning data.

교육 기관: Li G

2017년 1월 12일

Very helpful and pragmatic.

This course gives a general idea on how to get and clean data in r, and specifically taught me how to use "dplyr" and "tidyr".

The assignment is very helpful, too. It forced me to use the knowledge I learned in this course, might be a little bit of hard for a beginner though. Nevertheless, you can still achieve a 100% score!

교육 기관: Tai C M

2017년 9월 16일

I am very happy to go through this subject not because of the certification but I learned the steps to import and clean the data. Although this subject is no rocket science, a lot of the data available on the web will require the knowledge that I learned in this subject to enhance the integrity of the data that anyone can download from the web.

교육 기관: Anthony S

2016년 11월 2일

Learned a lot! I have now dedicated more time to becoming a data analyst, and eventually a data scientist. The materials used in the videos were helpful and current (for me at least, 30 years young). I have started doing more learning on the kaggle platform as well as doing some hands-on Hadoop related training. Thanks to the professors!

교육 기관: Carlos M

2017년 10월 19일

This course is fantastic! Through it was possible concretely to apply the concepts of BigData through the tool proposed for the course. Due to various difficulties I had to leave. But I'm coming back with all my might. Congratulations to all teachers who make no effort to pass on knowledge in a substantial and substantial way.

교육 기관: Rodney A J

2017년 6월 6일

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: Murat Z

2018년 2월 11일

Great course for data mining and cleaning. If you planning to take Reproducible Research course, I'd recommend to at least audit that course's second week for markdown and knitr skills prior to taking Getting and Cleaning Data course, coz you're going to face need for those skills during the course project.

교육 기관: Sachi B

2018년 2월 19일

Good intro to several commands needed for cleaning and preparing data. Final assignment was challenging enough that made me dig deeper into commands. Since there are several ways of accomplishing the same task in R, grading the other students helped see what others have done - some of them were slick!

교육 기관: Aki T

2019년 10월 24일

This course was excellent and fundamental in order to even start a data analysis. It sets the foundation for how to read and treat the data, which is as the instructor mentioned, often overlooked. Thank you very much for taking the time to break the cleaning process into each comprehensive pieces.

교육 기관: Nino P

2019년 5월 24일

A bit tough course with topics of getting the data since I don't know much about file types, but cleaning part is a must do for every data scientist. dplyr and tidyverse is the base of R and nowadays I only use dplyr for my data wrangling. Highly recommendable course and specialization.

교육 기관: Sudheergouda P

2018년 12월 31일

The course project was really helpfull in understanding how the data is presented to datascientists. Now to get the jist of the data we have to go through assembling, cleaning and cutting the data.. It was a challenged to understand the data.. assembling the data was a lot of fun in R..

교육 기관: Fernando V

2016년 12월 14일

A great course. I mean, It has not been easy, I have spent a lot of time in front of the PC practising and doing exercises, but this time and the tools that I have learned make me much more agile and confortable with R, and I have seen the big possibilities that this language has.

교육 기관: Christopher L

2017년 7월 17일

great course, I am fairly familiar with R in my line of work but this was a great opportunity to practice web-scraping. I might even switch from a dplyr-centric wrangling workflow to one centered on data.table in my personal and professional work. more compact and faster!

교육 기관: Carlos M

2016년 12월 21일

Difficult but valuable. You will be watching the videos repeatedly and become a regular at StockOverflow but it was completely worth it. Getting, cleaning, and processing data is pretty much 80%+ of the job, this course's information is vital to any future data worker.

교육 기관: Gilvan S

2017년 2월 11일

Excellent course. It gets through the "dirty job" of obtaining data from diverse sources (including API, web, and others), cleaning it, and transforming it into a "tidy" dataset. Highly recommended, along with the R programming course (which you should take first).

교육 기관: Scott C

2018년 2월 17일

Good overview of what it means to get and clean your own data. Really enjoyed the final project as it challenged you to, with minimal guidance, think through what a tidy dataset really means, and figure out how to make that happen with the dataset you are provided.

교육 기관: Tim S

2016년 3월 23일

For someone with no programming background and limited experience working with data, this was a challenging, sometimes frustrating, course. But perseverance through the struggle can end in a deep sense of satisfaction. Happily, this is how it was - quite rewarding.

교육 기관: Gbolahan

2016년 9월 7일

Wonderful course. gets you through the basics and beyond in getting and cleaning data from diverse sources. Very well thought and explained. There is a lot to be learnt from this course, and it requires devoting a good amount of time to let the material sink in.

교육 기관: Diego A S R

2020년 7월 4일

Good course, but needs an update. Week 2 was really difficult compared to what was explained in the lectures and regex expressions should be explained using R, it was a little hard to learn to use them directly in R. I feel that I learned a lot in this course.

교육 기관: Renzzo S S

2020년 11월 16일

Excellent course! i learned a lot with the packages mentioned dplyr, tidyr, readr, lubridate. the swirl package is perfect to learn by doing and the assignment is very challenging and it is good because it incentivates you to research deeply and learn more.

교육 기관: Randal N

2018년 1월 23일

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: Keat C C

2016년 11월 7일

Really can learn practical skills! I like that each sub course of data science specialisation just focus on a certain areas and takes only 4 weeks, this way I won't be overburden between work and learning, and also easier for me to absorb the new skills.

교육 기관: Waleed A

2018년 1월 31일

Another brilliant course from Johns Hopkins University in the data science specialisation. Data preparation is a step where an analyst may spend considerable time before beginning any analysis task. I found this course useful and practical. It provided

교육 기관: Daniel M D V

2019년 9월 3일

Excellent! From my point of view, this is the best course so far. The general concepts that are thought here can be applied to any programming language you use for data analysis. The specific R concepts really shows the power R has to manipulate data.

교육 기관: Kunal P

2019년 12월 15일

This was one of the best class. Recommend more side reading material on data. SWIRL has a reading link but the link is not provided anywhere else on the board. Also, it would be beneficial if the links can be made clickable in lecture slides. Thanks.