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

33,148 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


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.


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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6426 - 6450 sur 6,978 Avis pour Les outils du scientifique des données

par Oliver K

19 oct. 2016

Gives a good overview of topics and the specialisation, however is still very basic. I'm looking forward to the next advanced courses

par Matt S

14 mai 2020

Some of the information for this course seemed to be missing and I felt I had to either guess a lot or search the internet for help.

par Alejandro S

17 mai 2016

Good as just an introduction to data science. Some more exercises using Github, maybe some collaborative works would have been nice.


21 mai 2020

The "robot voice" speaks really fast making me having trouble to understand the content several times. Overall it's a great course.

par Ioannis V

31 déc. 2017

gives some good information but the git section isn't really well made and it could have some improvements on sound and quality

par Brandon D

16 févr. 2017

Very basic overview of the tools and installation of them. Should be an optional course rather than part of the specialization.

par Baktygul A

9 juil. 2020

Peer-review assignment questions leave out some assumptions; it took me a while to figure out what exactly was expected of me.

par Anmol A

25 juin 2018

This course was a beginner level course and the difficulty level was quite low and in depth detail should have been provided.

par David R

4 sept. 2017

Extremely basic, should likely be a pre-req for non CS/IT types but could easily be summarized for more experienced students.

par Lluís G

2 sept. 2016

It is a good introductory course, but it could be optional for people with some experience in the field, as it is very basic.

par Alberto G

8 févr. 2016

The real basics of data analysis. The course is not bad I would just say it may be too simple even for an introductory course

par Rajeev J

15 sept. 2018

Didn't get an awful lot from this course. The videos have a lot of information which are not directly related to the course.

par Bob D

5 févr. 2016

This is a good introductory course to some of the tools but it doesn't go into the details of R programming or Data Science.

par Hassan T

21 avr. 2022

The content was good but they use AI voice which wasn't interesting at all. It was boring and I fell sleep a a lot of times

par Чмуров М В

21 sept. 2019

не представляет ценности в качестве отдельного от специализации курса. весь курс является просто введением по специализации

par 현 허

22 déc. 2017

It was too short and too easy, even though I didn't know how to use git. Only thing I learned is how to use git and github.

par Yuchen Z

26 mars 2016

Only include very basic contents, doesn't need 4 weeks to finish this course. More like a one or two day induction session.

par Marie-Morgane P

4 déc. 2016

Basic introduction to the specialization. It was way too simple for me since I already have knowledge in machine learning.

par Calvin K

10 déc. 2019

Please get rid of robot voice, it's awful.

Aside from that, very helpful and informative for preparation in other courses.

par Natanael M D L U

15 sept. 2019

This course is very introductory and very short, so that most of the things presented in the course were familiar to me.

par Daniel N

7 nov. 2016

illustration is not enough for the commands. More schematic description could help understanding the course much better.

par Mingyu Z

18 sept. 2016

It is not clear enough for a greenhand to understand, especially about installing Git on Mac or pushing files to Github.

par Samuel S

15 avr. 2016

Very light workload if you're technically competent. I would have liked to have had more to do with the math and such...

par Lerata M

30 déc. 2020

I found the introduction fruitful particularly to a person who knows nothing about Data Science, keep up the good work.

par Tanay J

28 avr. 2020

The course is very preliminary. I think more programming should be thought in this course. It's just very theoritical.