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.
DH
Feb 1, 2016
Easy, mostly instructive Course. The Assignments and quizzes are quite good, and illustrates the lessons very well.
See the videos for general presentation, but use the energy on the excersizes.
By 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.
By Cintia K
•Mar 9, 2021
Unfortunately the course's lectures are quite outdated, so you won't pass week 1 without all the research done by yourself.
By Ruwaa I
•Aug 18, 2020
I learned "ask Google" and dplyr, nothing more. Not as satisfied as with the other courses in the specialization.
By Adrea G
•Jul 28, 2022
I started this course but I don't feel that the material covered reflects the material tested in the quiz.
By Gianluca M
•Sep 19, 2016
The only interesting part was dplyr. The rest was too confusing, with lots of lists and no explanations.
By Adam M
•Jan 17, 2020
The information in the lectures is very stale, which makes it extremely frustrating to learn from.
By DESIREE P
•Mar 10, 2021
Messier than the 2 previous courses. Lacks explanations for codebook in the peer-graded exam.
By Sudarshan P
•Dec 5, 2017
The course material needs update. There are code snippets that do not work.
By Aditya D
•Sep 18, 2017
This course could have been better. It was all textual and it got boring.
By James C
•May 29, 2017
Final assignment is not well detailed, and may cause confusion.
By Guy P
•Mar 3, 2016
This course lacks projects to implement the skills we learn.
By Lee D
•May 18, 2016
The course was a bit mixed in terms of its quality.
By Colin H
•Oct 21, 2020
Guidance for assessments could be a lot better
By Adam K
•Aug 25, 2019
Very poor instructions for assignments.
By Rafee S
•Feb 25, 2019
waste of time for software engineers
By Maximilian P
•Jul 11, 2018
Too many things in one place
By Sergio B
•Nov 17, 2017
Worst class in this series.
By Michal K
•Apr 29, 2016
too superficial
By Leandro J G D
•May 12, 2020
Lacking focus.
By Warren
•Aug 5, 2016
Boring.
By Walson Q
•Nov 29, 2018
2
By Dan H
•Jan 16, 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.
By 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
By Abdulaziz M A A
•Jul 2, 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.
By Ryan N
•Oct 29, 2021
Course content is ok except for the week 2, quite confusing. Not very detail. Quite a few slides asking you to read up yourself from other sources.
And for the quizzes, mostly beyond the scope of the course.
Project wise, coding part is fine. The part that is totally not fine is the project requires you to prepare codebook and README, without any guidance in any videos in this course, or courses prior to taking this course. All you need is to read up yourself from other sources. The community are assuming people who are taking these courses have good knowledge in programming related work.