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.
By Denis S C
•Nov 1, 2017
Explanation could be more elaborated like the earlier courses
By JP B
•Aug 6, 2016
Not well explained.... Previous module was better structured.
By Andrew T
•Feb 1, 2018
Useful.
Too much talking. Not enough integrated exercises.
By Ryan W
•Oct 24, 2018
Mostly just R programming with data science in passing.
By Thomas G
•Aug 19, 2016
Very usefull but can be technical and discouraging
By BIBHUTI B P
•May 30, 2017
needs little more real time scenario examples..
By Pedro V Q d C
•Nov 9, 2016
Course is too simple, should be more extensive.
By Supun A
•Sep 1, 2022
peer review assignment is not getting reviewed
By Madhubalini V
•Oct 6, 2020
practices is much needed to complete projects.
By Dr. M H A J
•Jul 2, 2018
Amazing, Kindly update the versions always.
By Ahmed A
•Jun 14, 2020
I THINK THE COURSE NEED TO BE UBDATED
By Ivo G G V
•Jun 20, 2019
It needs an update on some libraries.
By Mario P
•Dec 9, 2017
Useful, but a little boring.
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 Mike 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 Simon J H
•Sep 26, 2022
This course is by far the least polished and engaging course I've taken on Data Science in Coursera. It just feels like it's 'phoned in'. Like the lecturer isn't really bothered with making it interesting, and just wants to reel off all this stuff as quickly as possible.
Then there are things that are just sloppy - like the section on Regular Expressions - they cover them, but then don't demonstrate their usage in R even once. Like - what function(s) can I use this stuff in? Then, at the end of Regular Expressions, he talks about turning off the 'greediness' of the * operator, but then doesn't even bother to show what that means via an example. It's like he just couldn't wait to finish the video.
I'm doing this course as part of the 10-course specialisation, but if the next courses are this flat and boring I'll probably pull out.
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.