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Avis et commentaires pour d'étudiants pour Obtenir et trier des données par Université Johns-Hopkins

7,929 évaluations
1,311 avis

À propos du cours

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....

Meilleurs avis


2 mai 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.


25 oct. 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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1176 - 1200 sur 1,274 Avis pour Obtenir et trier des données

par Pedro V Q d C

9 nov. 2016

Course is too simple, should be more extensive.

par Madhubalini V

6 oct. 2020

practices is much needed to complete projects.

par Dr. M H A J

2 juil. 2018

Amazing, Kindly update the versions always.

par Ahmed A

14 juin 2020


par Ivo G G V

20 juin 2019

It needs an update on some libraries.

par Mario P

9 déc. 2017

Useful, but a little boring.

par KIM D H

22 juil. 2017

its so hard for beginner to

par Antoine D

3 sept. 2016

Interesting but too simple.

par Liliana B S

4 mars 2016

Sometimes is hard to follow

par Dinesh B

13 mai 2017

The assignment was tough.

par Hussien E

11 sept. 2019

A little hard to follow

par Naman D D

9 juin 2020

Too much repetittion.

par Sujeet S

7 janv. 2020

Too tough

par Mike E

6 sept. 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 - 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.

par Bill C

28 sept. 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.

par Marcelo S

8 déc. 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.

par Marc F

15 mai 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.

par Thaer Z

13 oct. 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.

par Greg R

29 juin 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.

par Willie C

21 janv. 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.

par Matt B

14 mars 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.

par Lyn S

10 août 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.


11 oct. 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.

par Valentin D

19 janv. 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.

par Shawn L

12 avr. 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.