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Getting and Cleaning Data(으)로 돌아가기

존스홉킨스대학교의 Getting and Cleaning Data 학습자 리뷰 및 피드백

4.6
별점
7,004개의 평가
1,101개의 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.

BE

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.

필터링 기준:

Getting and Cleaning Data의 1,062개 리뷰 중 51~75

교육 기관: Gilvan S

Feb 11, 2017

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

Feb 17, 2018

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

Mar 24, 2016

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

Sep 07, 2016

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: Randal N

Jan 23, 2018

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

Nov 07, 2016

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

Jan 31, 2018

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

Sep 03, 2019

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

Dec 15, 2019

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.

교육 기관: Martin H

Aug 14, 2016

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.

교육 기관: Oleksandr K

Apr 15, 2018

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.

교육 기관: Kristin K

Aug 04, 2017

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.

교육 기관: Kang I B

Jun 08, 2017

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!

교육 기관: Jan K

Mar 07, 2017

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.

교육 기관: Miguel C

Dec 20, 2017

This is a very complete course. It covers the basics of what you have to know to adquire data from different sources and filter that data to be used in further steps of data analysis. It offered great notions on Data Mining also.

교육 기관: Tim S

Sep 17, 2017

I learned a lot. The videos were clear and helpful. The assignments were just the right level, not too easy and not hard but still challenging.

The swirl package for interactive practice/learning is also very helpful. I Love it!

교육 기관: Dmytro D

Mar 15, 2016

I am happy now with the single file HTML Documentation for the whole course, generated from md-Files in the cloned repo

https://github.com/DataScienceSpecialization/courses/

It is much handier than the standard downloadable PDFs.

교육 기관: Dominic C

Aug 01, 2016

Using R with training through your course seemed almost too easy, your book also greatly helped, thank you for such a well designed course which is so practically based and geared towards commercial programmers like myself.

교육 기관: Орехов А И

Mar 12, 2020

This course is very interesting and not as difficult as it seems. I learned many new stuff about data analysis in R, as well as how to work in swirl, something I have never encountered before. Otherwise, awesome course! :)

교육 기관: Vinayak

Jul 26, 2019

Great content, challenging assignments and quality videos. Loved the coursework and grateful to have learned from such highly experienced professors. Thanks Coursera and Johns Hopkins University for making this happen!

교육 기관: Abhiram R P

May 17, 2017

Good course design, challenging material. I love the fact that the course doesn't spoon feed everything, we are encouraged to learn more on our own. This course gives you almost everything required to handle data in R.

교육 기관: Francisco M M

Oct 20, 2017

Me pareció un excelente curso, muy didáctico y con mucha información adicional para poder estudiar por nuestra cuenta para lograr una mayor profundidad en algunos temas en especial. Lo recomendaría sin duda.

교육 기관: Nicholas A

Oct 03, 2017

I really enjoyed this class. Cleaning data is not very difficult, but it is a very important aspect of Data Science. This class taught me the importance on making data easily readable on top of the process.

교육 기관: Herson P C d M

Dec 07, 2016

Excepcional, estes cursos estão abrindo completamente minha mente para novos horizontes, novas possibilidades. Enfim, estou cada dia mais motivado e mais entusiasmado com tudo de novo que tenho aprendido!

교육 기관: Hugo S

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.