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The Data Scientist’s Toolbox に戻る

ジョンズ・ホプキンズ大学(Johns Hopkins University) による The Data Scientist’s Toolbox の受講者のレビューおよびフィードバック

4.6
26,689件の評価
5,569件のレビュー

コースについて

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....
ハイライト
Foundational tools
(243件のレビュー)
Introductory course
(1056件のレビュー)

人気のレビュー

SF

Apr 15, 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

Sep 08, 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.

フィルター:

The Data Scientist’s Toolbox: 151 - 175 / 5,452 レビュー

by Kaushal C

Jun 11, 2020

The course provides a good introduction to the necessary toolbox required. It provides introduction to the Rstudio interface and Github version control system. The course helped me gain a lot of knowledge regarding Data Scientist toolbox, especially the version control system.

by Michael S

Feb 20, 2018

I found this course to be effective at getting the student to recognize the baseline set of tools, skills and behaviors expected in courses 2-10. Moreover, none of said tools, skills or behaviors fall outside the confines of typical and/or "in demand" experience. Nice work!

by Prithvi M

Mar 11, 2020

Great course to get started with data science using R as primary language. Good data practices are encouraged and use of GitHub for version control gives additional confidence to anyone wishing to preserve their work that leads them up to the solution to the problem at hand.

by Francisco M R O

Aug 27, 2018

It's an excellent introductory course for the specialization, I have recommended this course to a friend because I have found the content pretty useful. I will continue with the other courses of the specialization and I'm very grateful to have this opportunity from Coursera.

by Oyetunde A O

Aug 13, 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.

by Peres R B

Apr 03, 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.

by Suryadeep D

Mar 17, 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).

by AKHIL K

Apr 11, 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).

by Arthur D

Apr 11, 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).

by Anatoli K

Mar 14, 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.

by Samuel W

Jun 08, 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.

by Hrishikesh P H

Apr 16, 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.

by BHAGAWAT M

Jan 29, 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.

by Juan C J T

Jun 12, 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.

by Daisuke I

Mar 07, 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.

by Ahmed M K

Oct 01, 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.

by Joan S D C H

Sep 06, 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.

by Richard E H

Apr 27, 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.

by Mark K

Jun 14, 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.

by Rajat A

Jul 13, 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.

by Kevin C B C

Nov 06, 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.

by Roberto A

Mar 11, 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!

by Eduardo d S A

Feb 07, 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!

by Sandra N

Aug 22, 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.

by Drew W

Aug 24, 2019

The course was well put together and documented. My only critic is that I would like the lecturer to go over Git and Github more thoroughly as I had to do some extensive outsourcing to be able to figure out how everything worked. Overall, a very good course.