Chevron Left
Back to Getting and Cleaning Data

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

4.6
stars
7,815 ratings
1,277 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.

Filter by:

1151 - 1175 of 1,239 Reviews for Getting and Cleaning Data

By KIM D H

Jul 22, 2017

its so hard for beginner to

By Antoine D

Sep 3, 2016

Interesting but too simple.

By Liliana B S

Mar 4, 2016

Sometimes is hard to follow

By Dinesh B

May 13, 2017

The assignment was tough.

By Hussien E

Sep 11, 2019

A little hard to follow

By Naman D D

Jun 9, 2020

Too much repetittion.

By Sujeet S

Jan 7, 2020

Too tough

By Michael E

Sep 6, 2017

Professors did not do a lot beyond rehearsing what the commands did. More important, there were a lot of small things that would stop progress on the course unless you went deep into the forums - for instance, one of the files in the final project was illegible unless you used the right text editor. Final project was poorly designed in that the data were untidy but intended to stay that way (See "Should I decompose the variable names?" in Thoughtful Bloke's post at https://thoughtfulbloke.wordpress.com/2015/09/09/getting-and-cleaning-the-assignment/ - he is right about jerk and mag but wrong about time/freq, gravity/body, acc/gyro, and x/y/z, which are mutually exclusive members of the same set and thus values that appear in column names). I appreciate that this course, unlike other online courses, actually makes you think, but students should only have to think about topics germane to the course. Overall much more frustrating and time-consuming than it should have been.

By Bill C

Sep 28, 2016

This course is where the material starts to get difficult, and the learning materials fail to provide the structure needed. There absolutely HAS to be a better teaching method than "reading the slides of bullet-ed text that I'm also showing". No functional examples are provided in the lectures and the real learning content is linked out to web resources. You will have to Google your way through this class because the provided instruction will not contain answers to the quiz or exam questions. A real disappointment.

I also think that Coursera knows this, because this was the first course where they ramped up the e-mail encouragement campaign. Their data must tell them this is where people fall off the specialization. Rather than addressing with marketing and messaging, they should encourage the instructors to improve the course.

By Marcelo S

Dec 8, 2017

There is a lot of room for improvement. In an ironic twist, since the course is about "cleaning data," we are left to our own devices figuring out a lot of this very outdated material, broken links, codes that don't work, etc, so we have to google and search StackOverflow and forums to fill in the gaps and create a better course. I was subsequently asked to be a Mentor in the course, but I would rather the author of the course revise it, instead of having us work for free trying to help people get through outdated material. All the help is in the discussion forums already anyway, so I'm not sure why they need more Mentors. The saving grace of this course is that you will learn, if you are desperate to learn, and it is part of a greater Specialization that is worth your time.

By Marc F

May 15, 2016

I believe this course suffers from neglect. Rarely did I see any of the mentors participating in the group discussions even though there were plenty of questions. Furthermore, some of the quiz questons seemed incomplete or confusing. The project was no better. I feel like the course was recorded a few years ago, and not much done after that to fix flaws, even though they are probably well known. The material is useful, but it would be nice to have a set of notes or a text to go with the lectures. You will spend a lot of time searching the internet to compelte the assignments. Sometimes that is good, but other times a guide geared to the course would have been better.

By Thaer Z

Oct 13, 2019

I am done with this course. every week is the same thing. the lectures are a long list of references to other references. The quiz questions can not be answered without spending hours troubleshooting RStudio or searching the forum for help and hints to find out why the loaded packages or functions are not found. The quiz recommends to load packages that don't work or have dependencies that are no longer valid. I wanted to take this specialization to learn new data analysis techniques. if I wanted to spend my time searching the internet for answers I can do that without paying monthly fees. Good luck everyone. I am done. I will try a different course or field of interest.

By Greg R

Jun 29, 2020

The methodology of getting and cleaning data was good but the course materials were lacking and really outdated. Some of the material is 5+ years old and reference deprecated packages and functions or includes links to sites that have been long updated or no longer exist. I found myself spending a lot of time doing my own research on what packages to use. There is value in that.

The quizzes and assignments cover good topics but the instructions are pretty unclear as to what the ask actually is. It takes a lot of independent research and combing through the forums to gain clarity. It is very time consuming.

By Willie C

Jan 21, 2020

Not a great course. The lecture videos were dull and not very informative, and did not do a good job of preparing you for the quizzes at the end of each week. The lecture videos mentioned and linked to a number of external resources, but you couldn't click on the links through the videos, so that wasn't useful. The forums were much more helpful than the lecture videos when it came to teaching you what you needed to know. I understand why a course like this is essential to the Data Science specialization, but I feel like this content could've been covered in a much more engaging and instructive manner.

By Matt B

Mar 14, 2021

Have to say, very disappointed when comparing this to the first course. The first course teaches you the concepts and the quizzes/projects give you a great environment to learn new concepts while proving knowledge of the previous ones. This course so far has 20is minutes of videos per week that teach you 60% of what you need for the quizzes, especially true for the second week. Save time and use another resource for learning about APIs and other data resources.

By Lyn S

Aug 10, 2017

Not bad, but certainly not good. I cannot believe there is a style of teaching where you never get to see the best way to do something. I can slog thru the programming, but I doubt it's the best way to do something, but I never get to see how something should have been done. It's odd we have no feedback from prof and just 'grading' from other students who also are slogging thru without ever seeing the best or even some good ways to have done something.

By ALEXEY P

Oct 11, 2017

The instructor cares very little about the ability of his students to keep up with his explanations. The pace at which the material is presented is horrible, the amount of details is just the bare minimum. I do not think it would be too much work for the instructor to double or maybe even triple the length of the course videos. But he just does not seem to care.

By Valentin D

Jan 19, 2016

Instructor reads lectures in monotonic voice. The lectures themselves are just a series of cases of some R functions usage with no basics of Why you need to clean the data or real cases with complete examples how and where to get your data and what steps you can do to make it useful.

The course has a lot of links for tutorials in R. That's a plus.

By Shawn L

Apr 12, 2016

The project at the end requires actions that data scientists should know but does not actually talk about the items. For example the project "book". You hear about it but are not actually taught the right way to make one. At best case you are taking a guess and at worst you are learning bad habits or missing out on what should be in it.

By Chris M

Mar 5, 2016

Didn't really cover how to deal with messy data, e.g. if you need to join to datasets and have orphans, or you have no foreign keys between two datasets and you need to use fuzzy matching.

Basic validation was also not covered (i.e. making sure that your data covers all that you expect).

By Jason R H M

Aug 11, 2020

The explication in every lesson is really bad, and the exercise need more thigs that they explain, you must search the most of the tools in the course, if they make some videos or examples with all tools in the program, maybe can be better but in this moment is not good course

By Jonathan O

Apr 18, 2016

I saw two main issues with this course: 1) dated lecture videos, oftentimes with R code that can't be replicated using up-to-date packages, and 2) lack of thoughtful design: example after example after example after example doesn't really teach you anything.

By James O

Jun 20, 2016

The class is getting stale. The instructors didn't respond to questions on the discussion forums about quiz items, the majority of assessment items seem to be available on Google and 50% of the peer reviewed assessment I checked used plagiarized solutions.

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.