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

4.6
étoiles
29,981 évaluations
6,392 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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201 - 225 sur 6,250 Avis pour Les outils du scientifique des données

par Oyetunde A O

13 août 2017

This is a nice course and well taught by all facilities made available by the facilitators. As soon as am financially able to start to finish from where I stopped, I will activate my remaining course left to roundup Data Science Specialization.

I really appreciate. Thank you.

par Peres R B

3 avr. 2016

Basic course introducing the minimum tools to start your journey in data science. The course was very important for me to get up to speed with Git and GitHub. All the information was given in a concise and objective way, yet covered all basic important points of such tools.

par Suryadeep D

17 mars 2016

Might look trivial at first glance to more experienced users, but was very much essential for a complete beginner like me. Gives a nice overview of a somewhat overwhelming (and sometimes intimidating) field and equips you with the basic tools necessary (like how to use git).

par Andrea P

3 sept. 2020

Excelente curso, aumentó de manera óptima mis conocimientos y resolvió todas mis dudas, ahora tengo gran parte de las herramientas para llega a ser una buena cientifica de datos y aparte de que aprendí mucho sobre el tema, pude practicar el inglés y aumentar mi vocabulario.

par AKHIL K

10 avr. 2020

The "Data Scientist's Toolbox" offered by Johns Hopkins University is a good head start for the newbies in the field of Data Science. The course gives the brief introduction to various software used by a Data Scientist that is R, R studio, Git hub and Git (version control).

par Arthur D

11 avr. 2016

Very good introduction to data science. It gives a general overview on data and its problematics but also tips and help on how to start with the basic tools that will be needed (I haven't done any R programming and didn't have a github account so that was helpful for me).

par Bhavay S

22 juil. 2020

It is a very good course to get introduced to the world of data science. Working knowledge of R, RStudio and GitHub is covered in a very nice and organised manner. I feel more confident and equipped to proceed further and learn how to solve problems through data science.

par Anatoli K

14 mars 2019

Интересно было посмотреть как работает один из лучших исследовательских университетов мира.

Кроме настройки программного обеспечения много узнал об основных принципах науки о данных.

Очень понравился пример с Хилари Клинтон. Возможно это был роковой момент в её поражении.

par Samuel W

8 juin 2020

This is not a coding course. It is a course to bring you up to date with the logistics of using R: downloading packages, using RStudio, using GitHub version control, and familiarizing oneself with the overarching concepts of experimental design, statistics and big data.

par Hrishikesh P H

16 avr. 2020

A very easy to understand, nice and simple course. ample quizzes and puzzles available. A recommendation : please include a thing or two about RStudio Cloud. Especially, please include how to tie up your github repo to RStudio Cloud; as the procedure s different for it.

par BHAGAWAT M

29 janv. 2020

It's really enjoyable, a lot to know and a lot to discuss. The other links provided for more details are very much helpful. The feature of the discussion form is very helpful. Thanks, to Coursera and the team of Coursera for your high great work to open this platform.

par Juan C J T

11 juin 2018

Muy buen curso introductorio en el que se pueden observar las herramientas necesarias para realizar análisis de datos, además de que muestran quienes son Científicos de Datos en la actualidad y qué tipo de análisis realizan, todo adquiriendo la información de internet.

par Daisuke I

7 mars 2016

Setting up the environment is often the tricky part that deters people from moving into, or back into coding. This class provided me with a hand-holding needed to start coding again. I recommend this course as a kick starter for those who were on legacy environments.

par Ahmed M K

1 oct. 2016

What a great introduction. It needs a lot of reading and self developing to be able to do that project at the end. It's kind of difficult but you'll feel that you've really learned something that will be useful for the rest of your life. Thanks JH and Coursera staff.

par Joan c h

6 sept. 2019

Es un buen curso. te lleva de la mano pero no te da todo digerido en cierto momento debes buscar alguna solución para las tareas que te piden pues por razones de versiones ya no funciona igual.

Sin embargo el contenido temático es lo importante y me pareció perfecto.

par Richard E H

27 avr. 2018

A good introduction to analytical processes and tools. The course by itself, however, is only a first step. I find many threads begun but not tied together. I anticipate that the remaining nine courses will expand and consolidate everything opened in this course.

par Pedro A

11 sept. 2020

Es un excelente curso, te insta a ser ordenado en tu trabajo con el uso de las herramientas que existente para que podamos a cada proyecto que tengas y podamos refrescar rápidamente todo el historial con el control de cambios. ¡Excelente introducción del Programa!

par Mark K

14 juin 2020

The course is great at explaining the preliminary steps for setting up an R development environment and describing the basics of data science. Videos were paced well, not being too short or long, which allows the viewer to stay focused and interested. Recommended.

par bekir y a

16 sept. 2020

Quite helpful course in teaching the fundamentals of data science, do not expect to use statistical analyses programs effectively with the help of this course. This course's main aim is on teaching the fundamentals of data science just like we see in a university

par RCantu

14 sept. 2020

Super!, I was an excellent way to start the certification, and also a very good motivation to learn about contents included ( R, R markdown, github, control advance) . At the final of all, it is not possible to run if we do not to learn to walk. Thanks for it .

par Rajat A

13 juil. 2020

Very well paced course with a well structured approach to the toolkit. I would encourage people to take this course to get a hang of the basic working environment. It works even better if you already have a strong foundation in Statistics, and Research Methods.

par Kevin C B C

6 nov. 2017

A very eyeopening introduction to the discipline of Data Science. Hope this prepares me for R programming soon. :) I also realized how relevant this is today especially in the sciences, wherein one must have a good grasp in programming as an aid for research.

par Roberto A

11 mars 2017

I found this intro course really useful as a warm up and to get into the "data scientist's mindset". The only (minor) point for development is to devote more time to Git and Github, as some of the steps were not particularly straightforward. Well done though!

par Eduardo A

7 févr. 2017

I really loved the course. My peers were amazing. They always help and when they review your project they make sure that you will understand what you did wrong, explaining why and how you might gei it right the next time. Mr. Peng you are amazing. Thank you!

par Sandra N

22 août 2016

This is a fantastic way for individuals to get a leg up if they want a competitive edge in an ever-changing scientific environment. It is important to be able to use certain programs and code to some degree in order to be competitive using today's technology.