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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

4.5
21,150件の評価
4,218件のレビュー

コースについて

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....
ハイライト
Foundational tools
(243件のレビュー)
Introductory course
(1056件のレビュー)

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.

フィルター:

The Data Scientist’s Toolbox: 3951 - 3975 / 4,091 レビュー

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.

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Materials are getting out of date, especially with some of Github's new features.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 Dennis W

Feb 21, 2016

Very introductory. This material could have been compressed into 1 week.

by Markus K

Mar 10, 2016

Way too basic.

by Marek D

Mar 08, 2016

Nice introduction but actually very little content

by Shawn L

Feb 18, 2016

I think this course could have been done in two 30 minute videos. It jumps in with overviews but contain some high level items you won't understand until later in the course and it really doesn't give enough context to be meaningful at the time. It almost seems like it was thrown together without a clear mission of what should be in the introduction. Being a developer who has used some of the tools in this toolbox (Git, GitHub, Command Line) this intro really glosses over tools that most non developers won't understand. If I had a say in what should be in this intro it would be one video end to end of setting up the tools. The second video would be all about the history and logic and some of the applications we will be exploring without all the r formulas in the slides.

by Heather G

Mar 21, 2016

This should not be its own course, as it would be pretty useless if you were doing it on its own without doing any of the other courses. The end of course project literally being just to make a Github account and download R-studio could be quickly covered in the first week of the other courses.

by Freddie K

Aug 12, 2016

Very shallow overview, not really a full course I'd say.

by Nestor S

Mar 30, 2016

I didn't get much out of it

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 Tribs S

Sep 08, 2016

I thought this was very very basic

by matthieu c

Jun 03, 2017

Absolutely interesting, but a loss of time if someone already knows the basics.

by Cándido O M

Oct 02, 2017

Too basic material. I had to watch everything x2 faster to keep my attention. This course is just an overview of the topics that will be explained in the next courses, which could be much shorter in just one lesson or just avoid it. It is only useful to have R and RStudio installed and to introduce you to GitHub if you do not already know it.

I think it would be an improvement if you made the videos longer in order not to repeat yourself. Because sometimes you are constantly reintroducing a topic and never getting to explain much of it.

I hope that the rest of the courses be more direct and easier to keep my attention on, because I really what to learn about this subject!

Thank you

by Brian F

Jun 15, 2017

This course is very basic and takes nowhere near 1 month. I spent about 3 hours in total on it.

by Amir N

Jun 21, 2017

A little bit vague, could use more practice using git and git hub.

by Matthew C

Jun 30, 2017

Too easy and doesn't really prepare you for the next course.

by Yuan L

Nov 12, 2017

Not that useful. There is no need for videos. The content can simply be presented in one single PDF in a time-saving way.

by Grégoire M

Aug 31, 2017

A little bit too slow and too easy

by Dimitry W

Dec 05, 2017

Somewhat interesting to get an idea of what can be done with Git / Github, but I don't feel prepared to actually use it.

by George C

Jan 13, 2018

I personally think that this course should be better interwoven into the other modules of the data science specialization. It's a quick primer, but aside from that, not very valuable in terms of the information that it's providing. I wouldn't pay $49 to take this course.

by James C

Jan 07, 2018

Very high-level discussion of data science and useful tools.

by Andrew T

Jan 04, 2018

Basic setup of R and Git.

Prefer Treehouse's integrated workshop structure for tasks like these and/or youtube.

by Owen I

Nov 16, 2016

Is this entire course going to be watching videos of powerpoint slideshows, wrapped in a rather buggy website?

by Roy H

Jan 17, 2016

Dry videos. Most classes are someone showing how they do something their way, rather than guiding or teaching with the intent to have the student absorb and re-apply principles.

Very difficult for a student to absorb material from this video series

by Raj K P

Nov 14, 2017

showing - doing things live in the video would have been great .. it seemed like explaining a PPT by an instructor. You could have taken one data set and have done all shorts of things and then in the midst thrown some quizzes to student instead of going though all the discussion in one go