May 03, 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.
Feb 02, 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.
von Liam C•
Jan 29, 2020
Week 1 and 2 are completely worthless. They're cursory 5-10m introductions to topics that show you HOW to start to do something, but don't explain any commands or what is going on, it's just instructions to follow. This leaves you completely unprepared to do any actual work. Then you get the assignments and you basically have to go learn everything independently. The course info is useless. I skipped these. When I want to do the type of work they cover, I'll watch some tutorials and read documentation to actually learn it. They need to focus in on one or two topics (e.g. APIs, MySQL) and actually teach you the basics of them. The lecture videos even use weird syntax without explanation (e.g. using = instead of <-. Using par(), etc.).
Like the other courses in this specialization, you'll spend almost all of your time learning independently, and not using any of the materials provided. The discussion board is sometimes useful, but you can see how little work is done to improve the course there, as people point out errors and issues which are still outstanding months/years later.
von Michael E•
Sep 06, 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.
von 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.
von Marcelo S•
Dec 09, 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.
von 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.
von Thaer Z•
Oct 14, 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.
von Kyle R•
Jun 02, 2020
So far the worst of the series. The material is good and to the best of my knowledge it is useful to serve as a baseline for a data science career. However, the lectures are structured very poorly. Many of the links provided are outdated. The lectures have blue "links" in them where the data is discussed or subsetted, but that data is not provided and neither is the link. How is this considered reproducible? Is that not a component of data science? Also, the syntax used is continuously changed (the assignment operator is not consistent) and spacing is also inconsistent between classes. Just not the quality I'd expect for a course taught by experts in this field.
von Willie C•
Jan 22, 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.
von 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.
von ALEXEY P•
Oct 12, 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.
von 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.
von 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.
von Chris M•
Mar 05, 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).
von 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.
von 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.
von 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.
von 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.
von 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.
von Eduardo S B•
Oct 05, 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.
von Jason Y•
Aug 02, 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.
von Patti M•
Jan 04, 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.
von Sheila B•
May 07, 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.
von James K•
May 12, 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.
von 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!
von 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!!