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The Data Scientist’s Toolbox(으)로 돌아가기

The Data Scientist’s Toolbox, 존스홉킨스대학교

19,001개의 평가
3,811개의 리뷰

About this Course

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....
Foundational tools
(243개의 검토)
Introductory course
(1056개의 검토)

최상위 리뷰

대학: 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.

대학: 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.

필터링 기준:

3,684개의 리뷰

대학: Bhupendra Singh Purawat

May 20, 2019

Good for beginners.

대학: Mila Thittaya Buengbunyuen

May 19, 2019

great basic understanding of data information.

대학: Catherine Solano

May 19, 2019

Como puedo recibir mi certificado ? al correo

대학: Andhra Maha Vishnu Kakumani

May 19, 2019

Toolbox is a basic and involving course

대학: Daniel Mauricio Diaz Vela

May 18, 2019

Very basic course to set-up the necessary tools for the specialization. Nothing more

대학: Siddhesh Kulkarni

May 17, 2019

Nice course get to learn the fundamentals of data science.


May 17, 2019

it was great experience form me as a data scientist newbie. with structured lesson make me easier to understand

대학: Ariel José Arias Zepeda

May 16, 2019

Very intructive

대학: John Wu

May 15, 2019

Good foundation for analyzing scientific data

대학: Justine Marion Contreras

May 14, 2019

Excellent to start with the basics of R and Github, also it's very complete when starting in the most common used concepts of data science.