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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.

AM

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.

フィルター:

The Data Scientist’s Toolbox: 3901 - 3925 / 4,093 レビュー

by Luis C

Mar 24, 2019

it is a good course but need to show more examples of R. the course should show more empirice examples of the functions of R.

by Eric L C

Jan 28, 2019

Presentation great. Quizzes are idiotic. You take the quiz, it tells you that you got an answer wrong but does not tell you why most of the time -- so no chance to learn from your mistakes.

by ping c

Apr 09, 2019

The video wasn't very effective.

by Arun R

Jan 07, 2019

Very basic - Did not teach all the necessary things required with Git.

by Marie J

Feb 26, 2019

I found this informative but you do not get much in terms of service. One of the quiz has a technical issue and I made a complaint weeks ago, but I still haven't gotten a response. Nor has it been fixed.

by Todd H

Jul 15, 2018

I am simultaneously doing a course here and one on Udacity. In comparison, this course is much less enjoyable and efficient. There are several reasons for this 1) you never see a person present the material in the videos, it is just pictures of slides. This makes it feel less personal and enjoyable. 2) The lessons are relatively long and there are not opportunities to practice in between. Udacity, for example, has short 1-2 minute videos for each concept and then ungraded practice quizzes, which make it very clear what you are supposed to learn without feeling like you failed if you make mistakes. This saves you time so you don't have to go back into a 15 minute video to hunt for an answer to something. 3) The quizzes here test a lot of minutae. They are not always focused on the main points from the lecture. This can be frustrating because you may feel like you need to spend an unreasonable amount of time looking for answers to small points or get frustrated and feel like you are failing. That does not really make sense for an overview course. 4) The instructor often rambles or has side remarks. He sometimes forgets to give the proper background information for beginners. Takeaways or action points are not always clear. 5) This course feels unnecessarily long for what it is supposed to accomplish. It could be a list of programs to download and a very short summary of things you will learn in upcoming courses. Instead, you spend hours on this and feel like you walk away with no new technical skills.

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 Grégoire M

Aug 31, 2017

A little bit too slow and too easy

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 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 Karsten T

Feb 15, 2016

This could probably be compressed into a single week of setup for the R Programming course. There isn't much in terms of substantive learning here.

by Katherine F

Mar 17, 2016

Too short and easy.

by Vlad D

Feb 27, 2017

Too basic!

by Anna D

Mar 04, 2018

It's great to learn how to use GitHub but this hardly qualifies as a course.

by Selina H

Apr 12, 2016

It's more a preview than an actual class.

by David C J

Sep 26, 2016

This was really basic information. It's not really a 4 week course. It takes several hours. The info is necessary, but it's sufficient as a single week of content for a larger course.

by Ben V

Sep 13, 2016

Very very introductory. I didn't find the tooling aspects of this course particularly helpful, but I'm not in the target audience. It's length was misleading -- I completed the work in two days easily, but I am a technologist, and already had the tools installed. If you use GitHub and RStudio, the meat of the course is only about an hour of the lecture.

by Harshini S

Nov 22, 2016

A good intro to the tools required for a Data Scientist. However, could cover the usage of the terminal and Rstudio better.

by Josh H

Mar 03, 2018

Not very useful