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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



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....
Foundational tools
Introductory course



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.


Apr 24, 2018

This course was a good intro especially in setting all the necessary software for future courses. I suggest to read the manuals, books and other readings the profs suggest. The resources are helpful.


The Data Scientist’s Toolbox: 101 - 125 / 4,188 レビュー

by Karen L

Nov 08, 2018

This was my first experience taking a coursera course. I was impressed with the thorough and well thought out content. The course material was easy to follow and it was easy to stay on track. This was one of the best virtual classes I have attended. I am looking forward to the other courses!

by Rolin M

Aug 04, 2017

Thorough course introducing all practices related do data science.

A bit overwhelming but I mostly saw it as a lexicon of some kind; a resource to use again and again during the certification.

Hates off to the speakers who made a great job in terms of pedagogy in all video.

Max, form France.

by David B

Jul 25, 2018

Good foundation concepts for what will be required in DS according to the instructors. Good start point and presents basic challenges to getting you set up for the rest of the certification. Other courses will be required for more breadth and depth of concepts. Very good introduction.

by Ricardo J d S

Dec 17, 2018

Achei de grande valia, no meu caso, especificamente, por me colocar novamente em contato com a parte mais técnica da TI - venho desempenhando papéis gerenciais a algum tempo e tinha certo receio de alterar a configuração da minha máquina para ser um "laboratório" de ciência de dados.

by Farkhadov Z

Aug 08, 2016

Good course for begginers like me. All information is provided very simple and it's easy to understand. Also involves srudents not only looking videos but offer books. In addition you will need to search some information yourself to complete some tasks.

Thanks for this great course.


Dec 08, 2019

Even though it is a starter course to the specialization learned so many new things like amazon polly which is being used to generate these videos, R-markdown and how important is it to produce reproducible research.

A must take course for any data science aspirant

Happy Learning!!

by Ting L

Aug 24, 2018

It's a great course for beginners. I had little knowledge about data science. I didn't even know what was R and GIt. After taking this course, I had a preliminary understanding of them. If anyone wants to learn data science without any experience, this one can be your start point!

by Tristan I

Jan 17, 2020

All the information felt applicable to my current role. The main thing I gained from this course is that I feel more confident in the tools at my disposal as a data analyst. Additionally I learned about tools I had never heard of & how to utilize them, and for that I'm thankful!

by Becca M

Aug 31, 2018

I really appreciated the step by step through some of the very basics like downloading all the tools I'd need, using git and GitHub... things that looking around at free training are steps that are assumed and skipped and left me lost. Has built a lot of confidence to continue.

by Dominic C

Apr 25, 2016

Great way to learn R and become familiar with how to use it. As a developer with an understanding of Python, Java, C and C++ I could quickly see how to use R, how to extend it and start working with it today. Very good use of supporting tools like Swirl to assist with teaching.

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 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 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 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 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!