Chevron Left
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



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.


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.


The Data Scientist’s Toolbox: 276 - 300 / 4,942 レビュー

by Romeo P

Apr 29, 2020

This was a good course that started me on the right foot towards data science. I liked learning about version control, GitHub and git. Awesome lecture videos and nice to see AI at work.

by Roselyn B V

Oct 17, 2017

As an introduction to the data science tracking system, the course itself is superb in terms on the way it was outline especially to students like me who is new to this kind of subject.

by Nicholas A

Oct 03, 2017

Pretty straight forward class. Walks you through all the information you need to start programming in R. I still refer back to it every once in a while, going through the later classes.

by Stuart b

Feb 12, 2017

I have just started the course but so far the videos and education background references are exceptional. I highly review this website and university for its great learning experience.

by Daniel A A Y

Dec 08, 2016

Curso introductorio, que abarca el trabajo de proyectos y desarrollo de código/software, en base a Github, he introduce de manera precisa, los conocimientos básicos en minería de datos.

by Михаил

Feb 21, 2019

It very helpful course for first steps in data science. Moreover, It helps me knew about git, github and command line. Thanks to professors for handy materials and interesting quizzes.

by ketki

Apr 30, 2020

This is an amazing course for me to understand what tools a data scientists use . Gave a lot knowledge about Rstudio and many other things. Thank You so much Coursera for this course.

by Erfan S

Apr 02, 2020

This course is an amazing and practical intro into the data science and R program and is exceptionally critical for beginners who seek to dive further into data science in the future.

by Bibhu A P

Apr 02, 2019

This course is a primer on setting up the various environment required for learning Data science with R language. You can expect to learn the basics of Git and Github. R and R studio.


Feb 20, 2018

Absolutely fantastic way to start off a data science course. You dont need to be a techie for this, just common sense and you are all set. Cant wait to start the R Programming course.

by Jennifer C

Jun 27, 2017

After completing the course 1, I feel less fear to get on this field. The course explained the foundation of the data science is. It made me more comfortable to continue the course.

by David R

Sep 03, 2019

Excellent course giving a high level view of Data Science and the tools that will be used in the course. The AI instructor voice is a bit weird but you get used to it pretty quickly.

by Diego A Q

Jun 18, 2019

A great introduction to data science and also to the R Studio environment. R Studio is going to be very used through this specialization, so it is very useful to be familiar with it.

by Thiago

Jun 04, 2019

Leveling course to start in the discipline of data science very interesting. It contextualizes in a simple and objective way the necessary tools and environment for a data scientist.

by kelly s

Oct 20, 2017

Great Introduction to the tool's we'll need. I like it as a separate class rather than trying to get new tools to work or obtain new material on a timeline during the other classes.

by Paula C

Jun 21, 2016

Course teaches how to acquire the tools necessary to complete the Data Science specialization. Explanations were clear, and quizzes and assignments were straightforward to complete.

by Camilo A A

Jun 22, 2016

Es un excelente y necesario curso. Nos da luces sobre las herramientas que deberíamos usar para optimizar nuestro trabajo (en Big Data) tanto a nivel individual como colaborativo.

by Dean E

Jan 25, 2016

Don't just rely on the lectures. Use this course to introduce you to a bunch of tools that you'll need when doing data science, and then go study these tools in depth on your own.

by Victor O A

May 08, 2020

Awesome introduction to the field of data science.. good foundations that will definitely take me far as a data scientist contributing more responsively to improved health metrics

by Eric H

Jul 11, 2018

A brief but comprehensive fly-over of the specialisation, topped off with some software previews and installations. Bit of practical hands-on and we're good to go. 1 down 9 to go!

by Adedoyin O

Mar 24, 2018

This course was a very good intro to Data science for someone coming from a background with little coding experience. The instructors were engaging and assignments were practical.

by Pouria T

Oct 27, 2016

I had so much fun learning from this course. I think this course has been constructively laid out and the quality of the presented materials are at it best for such a vital field.

by Luis F O M

May 08, 2020

Es un curso bastante básico para aquellas personas que nunca han usado la plataforma de Rstudio, sin embargo tiene unos conceptos interesantes que merecen la pena tener en cuenta

by paomogu

Dec 31, 2017

This course is very good for somebody who don't have any experience for data handling.I think it gives me much help to let me go another step further in the road of data science.

by Sean O

Mar 12, 2017

Good course, but maybe this course and the following course R programming could be combined into an 8 weeks course as that one is took longer than 4 weeks and this one took less.