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Learner Reviews & Feedback for The Data Scientist’s Toolbox by Johns Hopkins University

32,986 ratings
7,046 reviews

About the Course

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

(243 Reviews)

Introductory course

(1056 Reviews)

Top reviews


Sep 7, 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 14, 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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5326 - 5350 of 6,942 Reviews for The Data Scientist’s Toolbox

By Matheus P S

Feb 12, 2018

Como curso introdutório das ferramentas muito bom. Achei um pouco longo desnecessariamente.

By Changlin Z

Aug 28, 2017

very good starting point for people does not have any background in stats and R programming


Jun 7, 2020

peers reveiw should be removed rather than that something other assingment should be given

By Samin Y

Apr 26, 2020

The course was super easy but super effective. Thank COURSERA for this amazing experience.

By Matt K

Jun 10, 2018

Instructors could do more demonstrations to make things more clear. Other than that, fine.

By Gautam J

May 22, 2018

This is course teaches the basics and installation only but is very good for that purpose.

By Diego G

Feb 5, 2016

Me quedó un poco vacio lo de GIT, tuve que averiguar más por mi mismo, pero esa es la idea

By 谢雳雳

Aug 19, 2021

Very good material!The machine generated course videos speak a little too fast to follow.

By Sameera K

Feb 26, 2019

This course appeared to have some irrelevant material, but perhaps it'll be useful later.

By Philip T

Apr 14, 2016

A good introduction to the subject area. It would be nice to see more real-life examples.

By Claudia Y P

Feb 24, 2016

Gives a good intro to Data Science and makes sure you get the essential tools downloaded.

By Enrique O

Dec 13, 2020

Excelente curso, bastante accesible para quienes no estén en el mundo de la informática.


Nov 3, 2020

Course is full of good information. The instructions could be just a bit more detailed.

By Stanislav G

Jul 10, 2020

There are some parts of the course especially on week 1 and 2 that are too introductory.

By michael s

Feb 10, 2020

Great course to get started with R Studio and Version control that actually makes sense.

By Soumyadeep B

Jun 7, 2018

It would be helpful if the courses on git are explained in a bit more detail

Thank You :)

By Deepti T

Apr 6, 2017

Very Good for basic understanding of Data Science and the tools used by Data Scientists.

By Cassandra S

May 25, 2016

Straightforward, interesting, and easy to follow. I wish it were a bit more challenging.

By Sara H

Nov 24, 2018

Gitbash is a little challenging, but Googling questions is helpful for troubleshooting.

By Ajendra S

Apr 5, 2018

Very basic stuff. Creator only focused on creating environment of the upcoming courses.

By Navroop K

Mar 17, 2018

A good introduction to the tools. Assignments are very helpful in learning the concepts

By Parker C

Oct 25, 2017

It was pretty easy, but essential to the rest of the specialty so I think it was great.

By Swagatam M

Apr 1, 2017

Great course, you get to learn about the tools used in the Data Science specialisation.

By Sharad S

Apr 19, 2021

Sometimes the voice in the video lectures goes as if it's not even reading a sentence.

By Periklis D

Nov 2, 2020

The course give you the first knowledge , which is necessery for the next data courses