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

4.6
stars
7,605 ratings
1,228 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.

DH
Feb 1, 2016

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.

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251 - 275 of 1,187 Reviews for Getting and Cleaning Data

By Lee W

Oct 4, 2017

Great course to introduce you to the various methods of loading and processing data in R.

By Ryan H

Sep 23, 2017

I really enjoyed this course. The instructors were good and the assignment was enjoyable.

By Alessandro P

Feb 9, 2016

Great course!

I think that cleaning the data in the right way is the key of data science.

By Patrícia A F

Apr 6, 2019

Great Course for you to learn in more detail how data processing works in Data Science.

By reem z

Jun 22, 2018

A great course and you learn exactly what the title says . I found it fun to work on It

By Tine M

Nov 14, 2017

Great course, I've learned a lot about analyzing data sets and creating tidy data sets.

By Robert K

May 1, 2017

Fantastic! I find myself using the information I learned in the class on a daily basis.

By Boris B

Feb 6, 2016

Great Course if want to know what data really is and how to handle it in the right way.

By Maxim S

Aug 26, 2020

Thanks, this course was great. It gave me enough knowledge and motivation to go forth.

By Alia E

Feb 27, 2017

Wasn't excited about it. But I've used and re-used the materials for work. Good stuff.

By Tseliso I M

Feb 2, 2017

Of the courses I have done so far in the specialization, this was the most practical.

By Carlos J T M

Feb 2, 2016

Very interesting material and basic knowledge on R to read files and produce tidy data

By GAGAN G

Oct 14, 2020

Very nice courses in coursera and fundamental concept are very helping for us. Clear.

By Tomas A M

Aug 22, 2017

Excellent course mates! Lots & lots of very useful info & examples! Thanks so much!!!

By Dmytro I

May 15, 2017

It's a great course, however, explanations to the final assignment were rather vague.

By Sambit C

Oct 12, 2016

A great course. Learned a lot. However student has to put an extra effort practicing.

By Kseniia K

May 3, 2016

Great course, more difficult than previous two, but also more challenging and useful!

By Wang J

May 1, 2016

Great practice for R programming and the MySQL part is extremely helpful for my work.

By Leonardo A

Aug 8, 2019

This is the best course so far. Very challenging project at the end. I learned a lot

By Jorge A B J

Jul 25, 2019

Very nice course! Would defensively recommend to anyone seeking this specialization!

By Puja G

Feb 6, 2018

Very useful to get hands on experience in data science to solve real world problems!

By Stephen A

Oct 3, 2020

This course gives all necessary foundations to kick start getting and cleaning data

By Abay J

Jan 20, 2019

Love quizzes and a course project. Working on them develops you as a data scientist

By Ajendra S

Aug 29, 2018

I really liked this course. This course helped me to understand the data wrangling.

By Tiago P F

Jan 3, 2018

Excellent course, with a very important focus on documentation and code versioning.