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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....
Introductory course
Foundational tools



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.


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: 3751 - 3775 / 4,103 レビュー

by Manohar

Mar 22, 2018

Nothing much important

by Victoria M

Mar 14, 2016

Doesn't provide a strong enough base for R Programming.

by Hernán S

Feb 29, 2016

Too easy

by Pragati

Mar 03, 2016

Students be more interactive.

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 Bonnie M

Jan 28, 2016

The content is very basic. The whole course took my around 6 hours to finish. I think the instructor should add more solid training on GitHub.

by Doug H

Feb 11, 2016

Too easy if you already know anything about github or Rstudio, although I do understand the need for an introductory course. The "Experimental Design" video was the only really useful part and contained quite entertaining examples.

by Dilyan D

Oct 09, 2016

This course sets the stage for the rest of the Data Science specialisation.

You get a lot of textbooks for free and they cover a lot of material.

The quizzes are a little bit underwhelming, especially the first week. Too few questions, testing some questionable knowledge (eg, what other courses there are in the specialisation -- hardly a required tool in the data scientist's box).

Overall, it's a good preparation for what is to come. It managed to whet my appetite for more , however I'm not sure the course is very useful on its own.

by Douglas P

Jun 27, 2016

It's a good preview, but very little is actually learned here.

by John A

Mar 28, 2016

This should be at most a 1 week course, that is free. Half the course is installing Rstudio and signing up for github. The other half of the course is simply learning what each course down the pipeline is about. Those lectures could just be tacked onto the description of each course and you would get the same thing out of it.

I think this course would be improved by more instruction on what git is and how to use it and maybe going over some fundamental statistical topics.

by Vivek K

Jan 08, 2017

Not really a course, should just be Week 1 in course 2

by patrice j

Feb 23, 2016

Good but needs more assistance with the students.

by Bill H

Mar 28, 2016

A necessary prerequisite for the other Data Science classes, but not really a standalone course.

by Antonio A

Feb 11, 2016

A good beginning to a promising journey

by Shaopeng L

Feb 28, 2016

The overall outline are great. However, the contents and requirements of this course are too simple to be integrated as a whole course. I think 1 lecture should be enough. I am looking forward to deeper introduction.

by marcelo G

Aug 15, 2016

A very basic overview on Data Science. You learn how to use git, rstudio, and other tools though. The other courses of the specialization are way better.

by Fred P

Mar 06, 2016

the lectures are full of the Prof misspeaking, this leads to you not knowing how to complete the task because the Prof can NOT communicate properly to us while we listening to the lectures... it seems like they completely missed the fact that NONE of us are data scientists...

Now your Audience......

by Lou O

Jun 21, 2016

It's ok. After the first lesson, I should be able to provide a clear elevator pitch with a high level understanding of what I can expect to accomplish (4 or 5 steps) as a Data Scientist. Instead, there was one slide that touched on this quickly, somewhere in the middle. What are the problems, how do I solve them, give samples.

by Bob D

Feb 05, 2016

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 Daniel M B

Nov 28, 2016

Demasiado básico para ser un curso formal.

by Oscar B A

Feb 10, 2016

It is useful to get to know the software that staticians use and some review about them but it doesn't teach you how to use them. A good introductory course for the specialization track but useless as a unique course.

by Yuchen Z

Mar 26, 2016

Only include very basic contents, doesn't need 4 weeks to finish this course. More like a one or two day induction session.

by John P

Aug 24, 2017

peer review was sporadic, had to redo several assignments based on language barrier

by Tan K T

Feb 24, 2016

Could be better.

by Vicki K

Mar 21, 2016

Basically if you take this course you are paying money to create an account on a website and download some software (both of which you can do for free). The rest of it is a preview of the other courses in the series. The quiz questions don't correspond to the information on the slides. I successfully passed the course, but I didn't really learn anything. Now I am debating on whether or not to continue to the R programming course after reading through the reviews of that course.