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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

4.6
22,395件の評価
4,512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
Introductory course
(1056件のレビュー)
Foundational tools
(243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: 3876 - 3900 / 4,391 レビュー

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 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 Sawyer W

Jun 15, 2017

This course should probably not be it's own course as it can be completed in one afternoon. It might be better suited as the first week of the R-Programming course (to make room maybe move the graphics talk to eda?)

by Deleted A

Apr 05, 2016

The course was fine, but I think it should be offered for free even if someone is doing the data science specialisation track. It is really just teaching you what data science is, and how to install a few programs.

by Chris C

Nov 01, 2018

There has to be a more engaging way of introducing course material. For example, by showing someone actually using these commands in the videos vs. just putting the Git, R commands in a power point bullet format.

by Sergio M

Apr 25, 2017

It's a good introductory course, but it's very basic and I feel that I paid a lot for a very basic experience. I do understand it is the first step in a full specialization but I think it can be more challenging.

by Jeff G

Sep 27, 2016

It is a very basic course to give you high level of what the course is going to cover and the tools that will be used throughout the course. If you have much programming background this course will be a breeze.

by Sebastien M

Sep 04, 2016

Well presented, but this course should be optional in in the specialization. There isn't really enough material to justify it, but it does cover the basics for someone with little to no development experience.

by Ghodratollah A

Mar 13, 2016

With many thanks to the instructors, I expected to learn more. I did not learn as much as a 4-week course in Coursera. Please include more materials and avoid advertising for other topics in the future courses!

by RISHABH G

Jan 21, 2018

The Course is very well designed and anyone who pursues it gets very well acquainted with the applications and tools . But i would like to suggest that this course can be completed in 7 days instead of a month

by Truong X

Jul 20, 2017

The length of the course, in my opinion, is a little bit too long. Actually it took me only 3 days to complete this course and I am not really a brilliant one. So I think maybe may will have the same opinion.

by Dave N

Mar 16, 2017

Not a bad intro; I don't know if anyone would benefit taking this as a standalone (or for an entire 4 weeks, for that matter). Still, it introduced some solid concepts for professionals and scholars, alike.

by mathias b

Aug 15, 2016

This is a really basic course. If you have never touch code before, it's more useful, but little is actually covered here and the gap between it's contents and the next class, R programming is dramatic.

by Chris H

Dec 15, 2016

Super basic, each week was only about 30 minutes of video lecture... but I think that was their goal? Bad form on coursera for making you pay to submit assignments that are autograded to begin with.

by Geoff S

Jul 27, 2016

This is a required course in the Data Science specialization. If you're planning to take that specialization, you should start with this course. If not, you shouldn't bother - there's not much here.

by Michal Š

Aug 12, 2016

As a software engineer I found this course a bit useless, but I do understand other people don't have the same background. Having said that, I believe it should be optional in the specialization.

by Yueming P

Nov 18, 2017

It's a great course. But the peer-graded setting of projects really delays the grant of certificate. It took me more than two sessions of waiting just to get a grade for the peer-review project.

by Michele B

Sep 13, 2018

Very basic, can be done in one day! However, we always need something simple to begin learning something new. Also, it was useful to have some guidance in the installation of the various tools.

by Alan Z

May 29, 2016

The course is basic, and quite simple. Some might say too simple. I think it should be about 1 week long. I already knew all the things going into it so it was easy to finish it over two days.

by Joseph S

Feb 01, 2020

The theoretical part of the course is good, but the quizz questions were simplistic and very hastily prepared. I would recommend this course as an optional module and not as a graded course.

by Constantin S

Feb 10, 2016

It's a very basic introduction. Would be nice to have the option to skip it for more advanced students.

Also the recorded lectures are really quite, so you have to turn up the speaker a lot.

by Pratheek G

Nov 16, 2017

Good Introduction to the basic tool set, Can be bit more comprehensive by giving an overview of other tools available to do the same operations and also why this tool set has been chosen.

by Fraida L

Nov 25, 2016

There wasn't much to learn that I didn't already know. There was a lot of talk but no real practical application (I guess except for github for people that didn't know how to use that).

by Olexandra M

Nov 27, 2017

This course coud have been provided as intro to R programming course or it could be just planned for 1 week. Anyway, overall it was ok though not yet extremely intense or informative.

by Lauren O

Apr 13, 2017

It was a good overview. I understand that it’s really just a quick intro into upcoming specialization courses. I wouldn’t take it alone. But I’m excited for the rest of the courses!