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Avis et commentaires pour d'étudiants pour Les outils du scientifique des données par Université Johns-Hopkins

4.6
étoiles
33,151 évaluations

À propos du cours

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....
Points forts
Foundational tools

(243 avis)

Introductory course

(1056 avis)

Meilleurs avis

LR

7 sept. 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.

SF

14 avr. 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.

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6401 - 6425 sur 6,979 Avis pour Les outils du scientifique des données

par Stefan H

7 mars 2019

I understand the text to voice automation was done due to cost reasons, but listening to the automated voice is VERY exhausting! Otherwise great content.

par marcelo G

14 août 2016

A very basic overview on Data Science. You learn how to use git, rstudio, and other tools though. The other courses of the specialization are way better.

par Ayush J

10 févr. 2016

This course should be a free trial for whole specialisation. IT will be more helpful for students to know what is further stored in the specialisation.

par Woszczyk H

20 juin 2019

If you already know your way around git and basic programming this is not a very interesting course.

I feel it should be included in the specialization.

par Peggy C

13 mars 2017

The word 'toolbox' made me think there was more in the course. 'Introduction' or maybe' Overview ' may have been more accurate. Good course otherwise.

par beth l

8 juin 2016

I was hoping to learn more stuff I didn't already know. This class is more of just a vague overview of the other courses. Can be completed in 1 week.

par Jarod T

25 nov. 2017

Its was pretty good. I'm not really sure how important it is to learn Git so soon but it must be used in the next classes so I am excited to find out.

par Raven W

15 avr. 2016

A good introduction to the course. Opening up quizzes to help feedback what we'd learned (for free learners) would have made the course much better!

par lcy9086

28 août 2018

Everything is fine

I think they had better not include the GitHub thing in it without clear explanation.

It takes me too much time on that assignment

par Andy C

20 nov. 2016

Not much of a course, I understand why it exists, but it's basically just getting setup with the environment. Almost not worthy of course status.

par Milad

28 mars 2016

it gives you the necessary tools and knowledge for just beginning the data mining course. so you cannot expect to learn about the process itself.

par Sahitesh R

17 avr. 2018

Less Content, should be more technical. Mostly repetitive from the the crash course in data science. Should have put an optional videos for git.

par SHREYAS A P

1 mai 2020

THE COURSE IS GREAT BUT SOMETIMES IT IS HARD TO UNDERSTAND CERTAIN THINGS AS THE LEVEL OF UNDERSTANDING FOR SOME CONCEPTS IS NOT UP TO THE MARK

par Yu T K

29 sept. 2020

I think this course has too many theory, I think it should contain more practical example for us to try....and too wordy

But overall it is fine

par Deleted A

12 déc. 2017

Too much material. Too soon. I am new to R and the stuff was a bit overwhelming. The course got easier as I advanced through the other courses

par Bonnie M

28 janv. 2016

The content is very basic. The whole course took my around 6 hours to finish. I think the instructor should add more solid training on GitHub.

par Rafaela C

5 août 2020

Estudar com essa inteligência artificial falando é IMPOSSÍVEL. E o material escrito só está disponível em inglês. Isso desvalorizou o curso.

par Martin H

8 août 2016

A bit odd this one. It hase some points, but most of the training is looking on what the other courses are.. Like paying for commercial :-)

par 杨燚

20 sept. 2017

The course was just fine, but I don't think we should spent entire 4 weeks on it. One or two week for this course would be better I think.

par Andrew V

22 févr. 2016

This course is very basic for a person with an IT background, but nevertheless might come in handy for people without relevant experience.

par Elbert B

16 sept. 2021

G​ood overview intro, but assignments only measured that you were listening, they did not require applying content to any new challenges.

par Jaume A

22 juin 2020

Difficult to follow the robotic voice at a speed of 1,5; the links simply don't workAnd, known bugs on LaTeX need to be found by googling

par Aishwarya K

25 janv. 2017

There is a slight lack of clarity in videos in terms of audio and also in terms of what exactly the author/lecturer is trying to convey.

par Raneem Y

29 juin 2020

thank you for the course it was useful. However the machine voice is really annoying and make fell uncomfortable and unfocused all time

par Siyang N

5 déc. 2020

Course content meets the standard. However, the computer voice is really terrible. I suggest you switch back to human voice teaching.