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.
교육 기관: 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!
교육 기관: 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!!
교육 기관: Seyed A T•
Jul 19, 2016
It is somehow just an extension on R Programming course, with many unnecessary details that will be forgotten in a few days after the course.
교육 기관: Sergio C d F•
Aug 23, 2016
The video is simple and good.
But the final project and some test are too hard based on material presented.
Also staff's support are not good.
교육 기관: Gianluca M•
Sep 19, 2016
The only interesting part was dplyr. The rest was too confusing, with lots of lists and no explanations.
교육 기관: Adam M•
Jan 18, 2020
The information in the lectures is very stale, which makes it extremely frustrating to learn from.
교육 기관: Sudarshan P•
Dec 05, 2017
The course material needs update. There are code snippets that do not work.
교육 기관: Aditya D•
Sep 18, 2017
This course could have been better. It was all textual and it got boring.
교육 기관: James C•
May 30, 2017
Final assignment is not well detailed, and may cause confusion.
교육 기관: Guy P•
Mar 03, 2016
This course lacks projects to implement the skills we learn.
교육 기관: Lee D•
May 19, 2016
The course was a bit mixed in terms of its quality.
교육 기관: Adam K•
Aug 26, 2019
Very poor instructions for assignments.
교육 기관: Rafee S•
Feb 25, 2019
waste of time for software engineers
교육 기관: Maximilian P•
Jul 11, 2018
Too many things in one place
교육 기관: Sergio B S•
Nov 17, 2017
Worst class in this series.
교육 기관: Michal K•
Apr 29, 2016
교육 기관: Leandro J G D•
May 12, 2020
교육 기관: Warren•
Aug 05, 2016
교육 기관: Walson Q•
Nov 29, 2018
교육 기관: Neil J•
Jul 23, 2016
R is really just the worst, and the instructors do not make it better. The code in this class is unreadable:
- too many one liners, because "it's faster to write", though harder for other people to read
- variables are named cryptic things like spIns or x, rather than names with meaning (eg, sprays.by.insect), again "because it's faster to type"
- way too many cases of "there is more than one way to do it", which just makes things confusing because the other ways tend not to be equivalent
What I'm most concerned about is that I've seen lots of poorly written code in many different languages: Java, C++, C, Python, Perl, and now R. But I've also seen really well-written code in all the languages *but* R, I have yet to see any code in R that is flexible, maintainable, and clear. Which leads me to think that no such code exists, or it's so rare that it doesn't matter. It is clear to me that if I am to do data analysis, then I will need a different set of tools; but because this specialization is taught entirely around R (the lectures are about R, not about higher-level concepts), then this specialization is not useful to me.
교육 기관: Daniel H•
Jan 17, 2018
This course is about getting data from the web and processing it using a computer language and packages in that language that are under active development. There is a github repo with course content and other electronic resources that are made to be easy to update. It has never been updated, even once since the course first went live 4 years ago. There are many broken links, several new features and bugs in packages that make lecture content obsolete or broken, errors found by students, etc. None of these issues have been addressed, even once, in any of the material, including the extremely easy to update content on github. This is disappointing and not very professional. Additionally, many of the notes are not particularly good to begin with. Much of it is essentially cribbed from other online tutorials, examples in the documentation, and in a few cases, someone else's (also broken) lectures. Take this course if you want a study group (the forums are actually quite useful) to help you go through 4 year old lectures rehashing online tutorials from 4 years ago about a topic that changes pretty quickly.
교육 기관: jake s•
Jun 29, 2016
There is a lot of fluff in this course and at the same time it assumes that you have knowledge and skills that are not covered in this course or in the previous two (e.g. github). I'm really disappointed in the quality of this course--specifically at how vague many of the instructions were in the quiz questions and the final project-- and that most the time when explanations were asked for on the message board the professors just did some hand waving and said that figuring it out was part of the assignment. That isn't teaching (online or otherwise). And if your instructions aren't clear, you aren't doing the job of an instructor when you pass the buck and try to sell it as "part of the learning experience." I hope this fall off in quality isn't reflective of the rest of the courses in the data spec.
교육 기관: Lindsay E M•
Jun 09, 2020
The first two courses in this specialization were good, but the third course, Getting and Cleaning Data, was honestly very disappointing. The lectures are extremely out of date (made in 2013, and it's already June 2020...), and a lot of the code in the lectures and examples no longer works correctly because of this. Beyond that, the "updates" posted by the mentors in the discussion forums are also out of date (2016) and have limited usefulness. This is a course that is meant to teach you how to acquire and clean data in the R program, and methods and technology from 7 years ago are not the standard that I expected - technology constantly changes and updates, and this course should reflect that (but clearly doesn't).
교육 기관: Grant I•
Jan 22, 2018
Made it all the way to week four and decided to drop this entire specialization. The data set in the final project is poorly referenced (despite the code book provided). The data set comes in 24 text files you have to merge (which isn't a problem in R) but what is a problem is when you don't understand what the variables and observations are. Perhaps if I worked in the medical field these measurements would mean more, but to a business major, they are incomprehensible with the limited documentation provided. So my assumption was, if I am having difficulty understanding what the final data structure should look like, others will be having the same problem......and its peer reviewed. How can I possible grade someone else
교육 기관: Abdulaziz M A A•
Jul 02, 2020
I have to date completed the first 2 courses in Data Science: Foundations using R Specialization.
Today I have cancelled my subscription for the following reasons:
1 Poor course design and delivery
Lesson contents inadequately covered and sourced, lecturers deliver a fast paced recordings with very little examples and references making it hard for beginner students to keep pace and find themselves unprepared for the required quizzes and exams.
2 Course materials needs to be updated and presented to facilitate learning , eg. often times students are referred to static links and too many many times new and un-familiar concepts/ functions are rushed thru with no introduction or explanation.