It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.
As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.
by Brandon D•
Very basic overview of the tools and installation of them. Should be an optional course rather than part of the specialization.
by Baktygul A•
Peer-review assignment questions leave out some assumptions; it took me a while to figure out what exactly was expected of me.
by Anmol A•
This course was a beginner level course and the difficulty level was quite low and in depth detail should have been provided.
by David R•
Extremely basic, should likely be a pre-req for non CS/IT types but could easily be summarized for more experienced students.
by Lluís G•
It is a good introductory course, but it could be optional for people with some experience in the field, as it is very basic.
by Alberto G M•
The real basics of data analysis. The course is not bad I would just say it may be too simple even for an introductory course
by Rajeev R J•
Didn't get an awful lot from this course. The videos have a lot of information which are not directly related to the course.
by Bob D•
This is a good introductory course to some of the tools but it doesn't go into the details of R programming or Data Science.
by Чмуров М В•
не представляет ценности в качестве отдельного от специализации курса. весь курс является просто введением по специализации
by 현 허•
It was too short and too easy, even though I didn't know how to use git. Only thing I learned is how to use git and github.
by Yuchen Z•
Only include very basic contents, doesn't need 4 weeks to finish this course. More like a one or two day induction session.
by Marie-Morgane P•
Basic introduction to the specialization. It was way too simple for me since I already have knowledge in machine learning.
by Calvin K•
Please get rid of robot voice, it's awful.
Aside from that, very helpful and informative for preparation in other courses.
by natanael m d l•
This course is very introductory and very short, so that most of the things presented in the course were familiar to me.
by Daniel T•
illustration is not enough for the commands. More schematic description could help understanding the course much better.
by Mingyu Z•
It is not clear enough for a greenhand to understand, especially about installing Git on Mac or pushing files to Github.
by Samuel S•
Very light workload if you're technically competent. I would have liked to have had more to do with the math and such...
by Lerata M•
I found the introduction fruitful particularly to a person who knows nothing about Data Science, keep up the good work.
by Tanay J•
The course is very preliminary. I think more programming should be thought in this course. It's just very theoritical.
by Christopher F•
Content is great for an absolute beginner. For anyone on the intermediate end of the spectrum it will seem very basic.
by Jad A•
Quite basic - but good overview of general theory. Don't do this on its own, it's quite useless as a standalone module
by fares a•
its just an introduction to R please make it more explanation to R even if there course about it
and thanks very much
by Lucas P•
The course accomplished its goal. Nevertheless, since it is a paid course I expected to find more theoretical content
by Khoa N•
very helpful but i think it is too short, i need some more concepts to fully understand what these tools used for
by Morgan D•
Lots of very general review information, not much new stuff. Did force me to start getting familiar with gitHub.