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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
21,671件の評価
4,335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: 3826 - 3850 / 4,209 レビュー

by leo0807

Jul 03, 2019

I think maybe because I have computer science background, so I think this course is too easy.

by Nikita

Feb 02, 2018

I don't really think that this amount of information should exist as a whole separate course.

by Lucio C

Aug 09, 2016

Good overview. But it is confusing for the first class when you have no idea about the topic.

by Maciej M

Feb 18, 2018

some information was interesting but in general I don't think it was crucial for learning R.

by Benny B E

Aug 01, 2017

If you don't know any thing about data science, good introduction, otherwise a wast of time.

by Yves-André G

May 27, 2017

A very simple course, focussed on installing the correct tools on your computer to learn R.

by Migdonio G

Feb 11, 2017

Too little material for 4 weeks. All this could've been written in a PDF instead of videos.

by Shahrooz

Jul 22, 2016

Overall the course content is good, but the power points are not engaging and interactive.

by Sadanand U

Aug 19, 2018

Very basic, may be a bit more use cases on Git would have been useful. But that's just me

by Uian S G

Nov 24, 2017

Few content for an entire course. I think this one could be together with R Programming.

by Andreas L

Dec 03, 2017

I am aware that this is the introduction to this topic but it was a bit long-drawn-out.

by Juan J E

Oct 22, 2017

I was already familiar with some content. it was a good starting point for may training

by Craig G

Jan 27, 2017

A good intro to the tools, but for anyone with prior programming experience unnecessary

by Debanjan D

May 25, 2019

Okayish course. This course will give you an introduction in RStudio and Data Science.

by João P S

Sep 07, 2017

Too few activities for the time allocated. I completed this course in 4 periods of 2h.

by Danyal F B

Jun 08, 2017

I think the project became very confusing since no examples were done in the lectures!

by Seckin D

May 20, 2016

I think this class is best for academic people. I did not find what i was looking for.

by John Y

Jul 08, 2017

This could be wrapped into one of the other courses since its just environment setup.

by Ryan C G

Jan 18, 2017

Pretty simple, the Univ of Michigan Data Science with Python set the bar pretty high.

by Ankush K

May 31, 2017

A little boring. Necessary if you have ABSOLUTELY no experience with data analysis.

by Drake O N

Mar 17, 2017

Good starter setup. Looking forward to the technical portion of the Specialization.

by John P

Aug 24, 2017

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

by Joao o

Dec 31, 2019

It`s too introductory. The methodology with an IA voice it`s not comfortable yet.

by Ivan S

Jan 12, 2016

highly recommended for newbs in any kind of development, otherwise waste of time.

by Sudarshan C

Jan 08, 2016

The course was very limited, it should have been combined with Introduction to R.