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Getting and Cleaning Data に戻る

ジョンズ・ホプキンズ大学(Johns Hopkins University) による Getting and Cleaning Data の受講者のレビューおよびフィードバック

4.5
7,940件の評価

コースについて

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....

人気のレビュー

HS

2020年5月2日

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

2016年10月25日

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.

フィルター:

Getting and Cleaning Data: 76 - 100 / 1,278 レビュー

by Sachi B

2018年2月19日

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!

by Aki T

2019年10月24日

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.

by Nino P

2019年5月24日

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.

by Sudheergouda P

2018年12月31日

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..

by Fernando V

2016年12月14日

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.

by Luis F T R

2022年7月6日

Getting and cleaning data is a great course, the lectures are clear and detailed also the weekly quizzes and final project are challenging. The teaches how to get data from different sources csv, txt, XML, JSON, web and APIs, read the data and transform it into some tidy data.

by Christopher L

2017年7月17日

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!

by Carlos M

2016年12月21日

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.

by Gilvan S

2017年2月11日

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).

by Scott C

2018年2月17日

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.

by Tim S

2016年3月23日

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.

by Gbolahan

2016年9月7日

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.

by Diego A S R

2020年7月4日

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.

by Renzzo S S

2020年11月16日

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.

by Randal N

2018年1月23日

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.

by Keat C C

2016年11月7日

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.

by Waleed A

2018年1月31日

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

by Daniel M D V

2019年9月3日

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.

by Kunal P

2019年12月15日

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.

by Martin H

2016年8月14日

Exellent course, which brings you to the next level of a Data Scientist.

Getting and Cleaning data principles can be used in alot of situations. I found the build up of this and the assignment at the end to be very well tought trough and important.

by Oleksandr K

2018年4月14日

Very good course and lectures. However, it would be good to have a book covering all of the material in this course. That would make work on final project much easier. In my opinion, it is impossible to finish final project in just 2 hours.

by Kristin K

2017年8月4日

This course solidified any gaps that were left from the R Programming Course and opens the world of data science to everyone in a very practical way. I really enjoyed the presentation of the material and am very happy I took the class.

by 강인배

2017年6月8日

This was so hard to me, because I didn't know anything about 'Making tidy dataset'. So, when I took a course project, I was struggling to find 'what should I do'. Comprehending raw data is so hard then you think, newbies! Be careful!

by Jan K

2017年3月7日

Covers a wide range of topics without loosing transparency. In my opinion requires more work than the other courses, but is really worth a go. You end up having a firm basis for working with data and learning more about the process.

by Tomer E

2020年6月21日

Very nice course.

helped to understand how to find sources of data (I found that extremely important), and strengthened my R skills.

It would be nice though to have the links which were shown in the slides available for the students.