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Opiniones y comentarios de aprendices correspondientes a The Data Scientist’s Toolbox por parte de Universidad Johns Hopkins

4.6
estrellas
30,624 calificaciones
6,528 reseña

Acerca del Curso

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....
Aspectos destacados
Foundational tools
(243 reseñas)
Introductory course
(1056 reseñas)

Principales reseñas

SF
14 de abr. de 2020

As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.

LR
7 de sep. de 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.

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6226 - 6250 de 6,387 revisiones para The Data Scientist’s Toolbox

por Anit B

27 de jun. de 2016

Introductory Course mostly around installation and setup for the other courses in Specializations

por Sergey I

10 de mar. de 2016

Maybe, I am already somehow experienced, but I think that the time I spent on that was a waste :/

por Brian F

15 de jun. de 2017

This course is very basic and takes nowhere near 1 month. I spent about 3 hours in total on it.

por Nayef

30 de mar. de 2017

i feel that the course need more explanation .. i got really lost in the begging of the HW

por Raviprakash R S

13 de feb. de 2017

This module is just enough material for 1 or 2 lectures with "How to get started" notes..

por Abhijeet S

17 de oct. de 2020

Course is okayish, automated voice is bit annoying and some contents are not up to date

por Mike J

26 de ene. de 2016

Good introduction of what is to come, but nothing too provocative or thought provoking.

por Urmil T

3 de ago. de 2020

Automated Voice is not helpful as it doesn't let you concentrate and makes you sleepy.

por Mohamed H

31 de ago. de 2020

The automated voice is extremely annoying but apart from that everything is good

por Abdallah A

2 de mar. de 2019

The instructor is an automated speaker, it was too bad, I couldn't focus at all.

por 潇湘夜雨动清愁

7 de may. de 2016

the speech is too fast to be catch up with and doesn't have much useful contents

por matthieu c

3 de jun. de 2017

Absolutely interesting, but a loss of time if someone already knows the basics.

por Scott T

5 de ene. de 2016

Didn't provide much info beyond the basics of git. Could have skipped this one.

por Patrick B

30 de jun. de 2016

Not sure this should be a course that is charged ....

on to the next one now.

por Anna D

4 de mar. de 2018

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

por Dennis W

20 de feb. de 2016

Very introductory. This material could have been compressed into 1 week.

por Arun R

7 de ene. de 2019

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

por Hugo R

28 de sep. de 2017

Isn't very usefull, I'm impatient to start the R programming courses.

por HARSH K S

27 de may. de 2020

This course is not much interactive because it includes boots voice.

por Neil J

16 de jun. de 2016

Extraordinarily basic. Entire thing can be done in about two hours.

por Ng J

18 de mar. de 2016

Might be useful for total newbies, but this was very simple for me.

por Rose G

11 de jul. de 2019

Not that interesting, but gives you the basis to install R and git

por Amir N

21 de jun. de 2017

A little bit vague, could use more practice using git and git hub.

por Kristin N

7 de jun. de 2016

Jumps around, doesn't put anything into "real world" examples.

por James C

7 de ene. de 2018

Very high-level discussion of data science and useful tools.