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The Data Scientist’s Toolbox に戻る

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



In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio....
Foundational tools
Introductory course



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.


Jul 22, 2017

Great Primer for what Data Science is about. It also provides the infrastructure of tools needed. This was what I was after, a way to provide other data scientist hardware and infrastructure support.


The Data Scientist’s Toolbox: 3926 - 3950 / 4,065 レビュー

by Lenka " P

Apr 19, 2016

It is a nice introduction, but the material is barely worth a one week orientation lesson (I have completed it in about 4 hours with watching all the videos, taking detailed notes, and completing the quizzes for 100%) . Why should we pay for a specialization preview, we can read info about the separate courses on our own? I am really looking forward the next courses in the specialization since I really need a good course in statistics and this seems to be one, but the first course should be eliminated. The installation of R and github account videos should be added to the next course as an introduction.

by valentine

Aug 27, 2016

Would like to have seen more material using git and git bash commands. More repetition here would be helpful. Seems like a lot of this information will be lost or forgotten when it comes time to use it, especially as it relates to the Data Science Specialization.

by Ashish S

Jan 24, 2017


by amaru f

Apr 25, 2018

i think was ok to start up

by Eva-Maria B

Jan 28, 2018

OK course. A brief overview, but the sequence of material isn't that well thought out in my opinion.

by Anit B

Jun 27, 2016

Introductory Course mostly around installation and setup for the other courses in Specializations

by Ng Z J

Mar 18, 2016

Might be useful for total newbies, but this was very simple for me.

by Lewis H

May 02, 2016

Sound is too quiet

by Alessandro V

Oct 22, 2016

It is too easy as a "university" course. It is much more like a pratictioner course. The final exam is ridiculous, really too easy.

It can be thought as a week course instead of a four week course.

by Thong K C

Oct 13, 2016

Too simple.

by Nicolas S

May 18, 2017

Not really useful.

by Allan P

Jul 26, 2016

Very basic even for people with no DS background.

Issues with quiz having passed and results showing as failed. Inability to speed up and move on to next module

by Derek P

Jan 06, 2016

Hard to follow with a lot of technical intructions right off the bat with inadequate explanation, a lot of "read more about this at <insert URL>." Videos were boring and the instructor was invisible just reading off the slides. Not very engaging.


May 08, 2016


by Anna K

Jul 13, 2017

Materials are getting out of date, especially with some of Github's new features. Instruction not clear in some lessons.

by Scott T

Jan 06, 2016

Didn't provide much info beyond the basics of git. Could have skipped this one.

by Adam D

Jun 12, 2017

If you can install R & RStudio and sign up for Github, then you're 80% finished with this course before you start.

by Tribs S

Sep 08, 2016

I thought this was very very basic

by Paolo A

Nov 07, 2016

I didnt learn anything about data science. I could have learned how to install all those tools by myself

by Hugo R

Sep 29, 2017

Isn't very usefull, I'm impatient to start the R programming courses.


Dec 30, 2016

I mean, it's replicated in the next classes, and it has silly questions in the practice quizzes. It's not worth it. Just kill this.

by Tarik G

Apr 28, 2018

I can see that the lecturer's intention was giving an overview by mentioning all different topics, however, it just got me confused. I wish it was more into a solo topic. It would be great if it was given only git/github lectures, so we, the students, can be more comfortable when it comes to uploading files in the following courses. I see in the discussion forums that github is a problem for most of the students in the forums.

by Daniel J R

Jun 20, 2018

Not very engaging videos. Superficial introduction to the mechanics of some tools without providing much context. Final submission did not work per video explanation. Need a more engaging presenter. Not quite at the level of Prof. Ng's Machine Learning course which I realy enjoyed and learned a lot from.

by Noah P

Mar 09, 2016

Not much substance to this course

by Julia S

Mar 01, 2017

This is really bad structured. As analogy - imagine a cookbook that says: in chapter 8 you'll learn how to cook pies, but here in introduction let me tell you how to add baking powder in them. It is not useless information it is just very out of place.

Learning some git commands was the most usefull in the course for me. (Though again, why would you first show the commands and just after that explain what's the tool for and where to download it?)

And by the way it takes half a day to cover all 4 weeks material (listened through all videos, installed the tools). Which is not bad, just of other users information)