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Learner Reviews & Feedback for Getting and Cleaning Data by Johns Hopkins University

4.5
stars
7,923 ratings
1,310 reviews

About the Course

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....

Top reviews

HS

May 2, 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 25, 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.

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1201 - 1225 of 1,273 Reviews for Getting and Cleaning Data

By izabela l

Aug 29, 2016

The code for the final assignment is peer reviewed which doesn't make sense. It should be reviewed by either a TA or some kind of application than can verify what you've done. Also, the assignments were a bit of a leap from the video tutorials at times.

By Daan v d V

Oct 7, 2020

Although this course is on a very interesting topic, it is quite outdated. Its lectures and examples are quite outdated; some web scraping examples are incompatible or don't exist anymore, and the described techniques are mostly (outdated) R libraries.

By Stephen S

Jun 27, 2016

The videos did not teach anything that was going to be on the quiz so it was like answering 5 questions at random using google. The lesson plans and project were very vague and too much time was spent trying to figure out what was even being asked.

By Shashank M

Jul 23, 2017

This is a very crucial part of the data science specialisation and I feel more hands-on exercises and quizzes should have been there. Small practice quizzes for testing incremental learning within a week should be there.

By Eduardo S B

Oct 5, 2019

In my opinion the structure of the course is not the best. I mainly dislike the fact that some libraries, packages, etc. (e.g. MySQL) are not trivial to install.

Still I learnt quite a lot, so I wouldn't say it's bad.

By le M N

Jun 23, 2020

the instructor of this course, unlike the other 1, is quite unclear about what needed to be done. a lots of the packages of the course are not up to date.

more quiz and exercise would be highly beneficial

By Jason Y

Aug 2, 2017

Mediocre presentation of tidy data, which is probably the most critical topic. Otherwise, its mostly just walking through what commands to use in R to load in various file formats.

By Patti M

Jan 4, 2017

This class needs more content, more explanation. It is clearly a very important aspect of Data Science, but the assignments were more complex than the given course content.

By Sheila B

May 7, 2018

I learned a lot but my usually happy & grateful attitude was sorely challenged by the fact that so many facts in the videos and obvious course material was, well, wrong.

By James K

May 11, 2020

Out of date material. Many links broken. Some of the functions taught are sunset. Week 2 was too surface level to do anything useful. Weeks 3 and 4 better than week 2.

By Joseph S

May 14, 2020

This course has a very interesting subject and a concise syllabus, but is very poorly prepared. I hope coursera will pass on the message to Johns Hopkins University!

By Albert B

Aug 14, 2016

Too difficult practical exercises with the theorical background given. I know that hackers skill should be used but it is too much assumption in the projects!!

By Seyed A T

Jul 19, 2016

It is somehow just an extension on R Programming course, with many unnecessary details that will be forgotten in a few days after the course.

By Sergio C d F

Aug 23, 2016

The video is simple and good.

But the final project and some test are too hard based on material presented.

Also staff's support are not good.

By Cintia K

Mar 9, 2021

Unfortunately the course's lectures are quite outdated, so you won't pass week 1 without all the research done by yourself.

By Ruwaa I

Aug 18, 2020

I learned "ask Google" and dplyr, nothing more. Not as satisfied as with the other courses in the specialization.

By Gianluca M

Sep 19, 2016

The only interesting part was dplyr. The rest was too confusing, with lots of lists and no explanations.

By Adam M

Jan 17, 2020

The information in the lectures is very stale, which makes it extremely frustrating to learn from.

By DESIREE P

Mar 10, 2021

Messier than the 2 previous courses. Lacks explanations for codebook in the peer-graded exam.

By Sudarshan P

Dec 5, 2017

The course material needs update. There are code snippets that do not work.

By Aditya D

Sep 18, 2017

This course could have been better. It was all textual and it got boring.

By James C

May 29, 2017

Final assignment is not well detailed, and may cause confusion.

By Guy P

Mar 3, 2016

This course lacks projects to implement the skills we learn.

By Lee D

May 18, 2016

The course was a bit mixed in terms of its quality.

By Colin H

Oct 21, 2020

Guidance for assessments could be a lot better