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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
20,757件の評価
4,151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: 76 - 100 / 4,020 レビュー

by Amanda C

Jan 08, 2019

This was a great introduction to the tools of the data science trade. If you are looking to get your feet wet, this is the perfect opportunity.

by Maria F G G

Jan 08, 2019

Good summarized introductory short course

by krishna k

Jan 08, 2019

good

by Jamie M

Jan 09, 2019

Great introduction to data science.

by Jorge R

Jan 08, 2019

Excellent prep course for DS

by Dan P

Jan 10, 2019

Basic stuff in a way, but quite enjoyable

by Jagat R S

Jan 10, 2019

I found git & git-hub tools very helpful.

by Adithya

Jan 09, 2019

helps me a lot knowing toolbox basics

by Shashank k

Jan 10, 2019

very basic course. can be done in 2-3 days if you study 3-4 hours daily.

by Adeyemi O A

Jan 10, 2019

Very good course for beginner in data science

by Joe D

Feb 20, 2019

An excellent introduction to r, rstudio, and the basic concepts and functions of github (online version control for personal or collaborative programming projects). Great course, informative videos, lots to do and experiment with, I highly recommend it!

by Ващенков В В

Feb 21, 2019

Info is compressed but it is still available for understanding and useful. But I think new students can have some difficulties with git or github, because theres some not so obvious commands like swap branch, commit changes etc...But it is also good for students to learn use Google and look forward for tutorials :)

by Михаил

Feb 21, 2019

It very helpful course for first steps in data science. Moreover, It helps me knew about git, github and command line. Thanks to professors for handy materials and interesting quizzes.

by Shivesh R S

Feb 21, 2019

nice

by Oliver G

Feb 11, 2019

Ideal for anyone who has never had any experience in the subject of data science. The course lays a nice foundation of what you need to know for the next courses in the specialisation. I would say it is 60% conceptual, 40% technical, which for me is just the right mix to get started on the subject.

by Sheila K

Feb 22, 2019

This course is engaging and difficult to put down. I was obsessed with completing this each week and actually finished a bit earlier. I consider myself nontechnical but the format was well done.

by Sakib S

Feb 12, 2019

Well organized and straight to the point with the various introduction to the field.

by Anand p

Feb 25, 2019

very nice lessons and very enjoyable.i enjoyed the lessons.

by NIHARIKA S

Feb 25, 2019

good

by parth m

Feb 25, 2019

.

by Ajayeswar R

Feb 24, 2019

Very good for the people who would like to know the working of R and Git from the scratch. The articulation between them is beautifully presented .

by Biplab H

Feb 14, 2019

Very Basic and easy to learn

by Antonio A

Feb 14, 2019

Excellent

by Jorge D B H

Feb 14, 2019

Buena introducción

by Eric P

Feb 14, 2019

The quickest yet most in-depth way to learn the RStudio tool kit and also learn the basic definitions that exist in data science.