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学生对 Johns Hopkins University 提供的 The Data Scientist’s Toolbox 的评价和反馈

4.6
34,065 个评分

课程概述

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....
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Foundational tools

(243 条评论)

Introductory course

(1056 条评论)

热门审阅

S

Oct 7, 2020

Great course content and very much informative with the different options of learning either through text or video. A good introductory course to the Data Science: Foundations Using R Specialization.

NB

Jun 2, 2017

Nice Course. Basics are very well taught in this course.Thank you JHU and Coursera for this course. I have decided to donate 10% of my first salary to coursera once I am complete this and get intern.

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5501 - The Data Scientist’s Toolbox 的 5525 个评论(共 7,177 个)

创建者 Xin G

Sep 25, 2021

Those tools are too basic which only helps newbies to warm up. However, it is quite detailed

创建者 Deleted A

Oct 22, 2020

In my opinion , the real person sound can be better to consantrate to the lecture deeply. :)

创建者 Rejuwan S

Sep 9, 2020

It will be good if these guys describe more about R markdown and github otherise it is good

创建者 Mari G F

Mar 24, 2018

Not a lot of practical application, but good conceptual intro with a little bit of practice.

创建者 Christian L

Nov 26, 2017

Good presentation of information and stressed the importance of "hacking" and self-learning.

创建者 Paresh D

Oct 28, 2017

push and pull of repositories should have been explained more clearly,rest course was great

创建者 Chris D

Jun 3, 2017

A little incomplete as a standalone course. Really forces you to pay for additional courses.

创建者 Elízio R d A

Mar 6, 2016

The course is great, I just think the course should has a little more content to be perfect.

创建者 Sanele K

Mar 13, 2021

A very good course that will well prepare you for future courses you'll take in the future.

创建者 Saad B M A

Aug 27, 2020

Amazing experience I got from this course. It is a perfect intro to the data science world.

创建者 tanya s

Jul 18, 2020

Good content. Easy Accessibility. Clear and precise learning. loved learning this course :)

创建者 Ben W

Jun 17, 2020

Good introduction to the tools that will be used in the rest of the courses in this series.

创建者 Hongxuan Y

Feb 5, 2020

This course would be quite helpful for those who step into data science for the first time!

创建者 Aman K

Jun 5, 2018

Good course, can be better with some small tweaks here and there otherwise well structured.

创建者 Nana A B

Jun 2, 2018

This course definitely gave me a great overview of what to expect in the data science field

创建者 Matheus P S

Feb 12, 2018

Como curso introdutório das ferramentas muito bom. Achei um pouco longo desnecessariamente.

创建者 Changlin Z

Aug 28, 2017

very good starting point for people does not have any background in stats and R programming

创建者 Anil M

Jun 26, 2024

Well done however some time audio is not relating to the contents displayed on the screen.

创建者 ATHARVA G

Jun 7, 2020

peers reveiw should be removed rather than that something other assingment should be given

创建者 Samin Y

Apr 26, 2020

The course was super easy but super effective. Thank COURSERA for this amazing experience.

创建者 Matt K

Jun 10, 2018

Instructors could do more demonstrations to make things more clear. Other than that, fine.

创建者 gautam j

May 21, 2018

This is course teaches the basics and installation only but is very good for that purpose.

创建者 Diego G

Feb 5, 2016

Me quedó un poco vacio lo de GIT, tuve que averiguar más por mi mismo, pero esa es la idea

创建者 AbdulAziz A

Nov 14, 2023

I didnt like the computer voice over. Overall it was an easy to follow course. Thank you.

创建者 谢雳雳

Aug 19, 2021

Very good material!The machine generated course videos speak a little too fast to follow.