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

4.6
étoiles
33,067 évaluations
7,061 avis

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

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.

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.

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6376 - 6400 sur 6,960 Avis pour Les outils du scientifique des données

par Dherbey C

24 avr. 2020

No subtitle in French as announced

It would be great to have the power point bigger when reading

The guide for connecting Rstudio and GitHub needs to be updated

par Islam D

22 févr. 2017

it could have been better if it was more hands-on learning, for instance I don't understand why did we learn CLI till now and how will I link it to my studies

par Madalyn Z

4 mai 2016

Might be a good introduction for those completely new to computational tools, but not useful for those with any background in git or R. Can be safely skipped.

par Quentin D

17 févr. 2016

Good course about getting the basics for the Data Science specialization, but a bit overpriced, as the content is low, and can easily be done in 4-5 hours.

par Julian C

22 janv. 2016

You don't really learn all that much, but then again I have experience with R and some data stuff already, so perhaps it'd be more useful for someone else.

par Farshad A

12 nov. 2016

It was a great start to data science but also students should have it in mind that the material presented in the course won't be enough to get through it.

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.