ジョンズ・ホプキンズ大学（Johns Hopkins University） による The Data Scientist’s Toolbox の受講者のレビューおよびフィードバック
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人気のレビュー
LR
Sep 08, 2017
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.
AI
Apr 24, 2018
This course was a good intro especially in setting all the necessary software for future courses. I suggest to read the manuals, books and other readings the profs suggest. The resources are helpful.
The Data Scientist’s Toolbox： 3951 - 3975 / 4,382 レビュー
by Jad A
•Nov 14, 2016
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
•Sep 08, 2017
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
•Apr 04, 2016
The course accomplished its goal. Nevertheless, since it is a paid course I expected to find more theoretical content
by Khoa N
•Oct 24, 2016
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
•Apr 19, 2016
Lots of very general review information, not much new stuff. Did force me to start getting familiar with gitHub.
by Aditya K R
•Mar 03, 2019
Super basic and boring stuff. Mostly talks about R Studio and GIT. Not of much help to those with IT experience.
by Ahmad A
•Oct 07, 2018
the voice is too low and the level of instructing are not for beginners, but with a lot of effort you could pass
by Rafael T M
•Apr 07, 2019
Very introductive. I hoped more about this course. There are interesting stuff but I'd rather more work volume.
by Sérgio M C d A C
•Jan 16, 2017
Github exposition is a little complicated. I believe it could be more detailed. But the rest is very well done!
by Deleted A
•Dec 29, 2016
Doing this course first doesn t make you anticipate how difficult could this speciality in the next courses :p
by PATHIK C
•Oct 13, 2016
There is practically nothing in this course to learn. It can be termed as a introduction to the specialization
by Andrey T
•Sep 06, 2016
The course is too easy to be called a course. Just an easy intro, which you can complete in a couple of days.
by Tamir L
•Jul 25, 2016
Very short, easy and introductory course. Gives a nice high altitude overview of the subject but little else.
by James M
•Feb 24, 2016
Not useful by itself, but grudgingly necessary to get you ready for subsequent courses in the specialization.
by Aritra D
•Jul 24, 2019
A little more depth on R and R studio and the rest and more data driven projects would have been appreciated
by Leyla C
•Feb 24, 2020
Easy introduction into R, maybe a bit too slow though. Course name is a bit misleading and not informative.
by Roman K
•Oct 10, 2017
The first 2 lectures (overview/introduction) are pretty good. The tools/practical material is very trivial.
by Bill S
•Apr 12, 2017
Mostly preparatory material and setup activities for the rest of the series. It's OK, but not a revelation.
by Shawn O
•May 28, 2016
Could be completed in a single day but spread across 4 weeks. I could understand a week but 4 seems silly.
by shrestha p
•Jan 18, 2020
It was great to know new terms and tools used in data science. However, the course is mostly theoretical.
by Jensen K
•Feb 08, 2016
Needed a step-by-step information sheet about what R Software and Tools need to be downloaded with links.
by Simin X
•May 06, 2017
It's only enter-level for people who don't know R. For those who already used R, it's not a good choice.
by John J O G
•Oct 28, 2016
Buen tema y contenido pero muy resumido o simplificado, se debería ampliar mas la 4 semana como mínimo.
by Abdullah M
•Dec 11, 2019
Good course for supporting the rest of the specialization. However, it has very little use on its own.
by M S G
•Feb 03, 2019
Would have loved it even more if there was an in-depth explanation of how to use GitHub using Git bash
