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

4.6
stars
32,663 ratings
6,969 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....
Highlights
Foundational tools
(243 Reviews)
Introductory course
(1056 Reviews)

Top reviews

SF
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.

LR
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.

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6276 - 6300 of 6,858 Reviews for The Data Scientist’s Toolbox

By Julian C

Jan 22, 2016

You don't really learn all that much, but then again I have experience with R and some data stuff already, so perhaps it'd be more useful for someone else.

By Farshad A

Nov 12, 2016

It was a great start to data science but also students should have it in mind that the material presented in the course won't be enough to get through it.

By Stefan H

Mar 7, 2019

I understand the text to voice automation was done due to cost reasons, but listening to the automated voice is VERY exhausting! Otherwise great content.

By marcelo G

Aug 14, 2016

A very basic overview on Data Science. You learn how to use git, rstudio, and other tools though. The other courses of the specialization are way better.

By Ayush J

Feb 10, 2016

This course should be a free trial for whole specialisation. IT will be more helpful for students to know what is further stored in the specialisation.

By Woszczyk H

Jun 20, 2019

If you already know your way around git and basic programming this is not a very interesting course.

I feel it should be included in the specialization.

By Peggy C

Mar 13, 2017

The word 'toolbox' made me think there was more in the course. 'Introduction' or maybe' Overview ' may have been more accurate. Good course otherwise.

By beth l

Jun 8, 2016

I was hoping to learn more stuff I didn't already know. This class is more of just a vague overview of the other courses. Can be completed in 1 week.

By Jarod T

Nov 25, 2017

Its was pretty good. I'm not really sure how important it is to learn Git so soon but it must be used in the next classes so I am excited to find out.

By Raven W

Apr 15, 2016

A good introduction to the course. Opening up quizzes to help feedback what we'd learned (for free learners) would have made the course much better!

By lcy9086

Aug 28, 2018

Everything is fine

I think they had better not include the GitHub thing in it without clear explanation.

It takes me too much time on that assignment

By Andy C

Nov 20, 2016

Not much of a course, I understand why it exists, but it's basically just getting setup with the environment. Almost not worthy of course status.

By Milad

Mar 28, 2016

it gives you the necessary tools and knowledge for just beginning the data mining course. so you cannot expect to learn about the process itself.

By Sahitesh R

Apr 17, 2018

Less Content, should be more technical. Mostly repetitive from the the crash course in data science. Should have put an optional videos for git.

By SHREYAS A P

May 1, 2020

THE COURSE IS GREAT BUT SOMETIMES IT IS HARD TO UNDERSTAND CERTAIN THINGS AS THE LEVEL OF UNDERSTANDING FOR SOME CONCEPTS IS NOT UP TO THE MARK

By Yu T K

Sep 29, 2020

I think this course has too many theory, I think it should contain more practical example for us to try....and too wordy

But overall it is fine

By Deleted A

Dec 12, 2017

Too much material. Too soon. I am new to R and the stuff was a bit overwhelming. The course got easier as I advanced through the other courses

By Bonnie M

Jan 28, 2016

The content is very basic. The whole course took my around 6 hours to finish. I think the instructor should add more solid training on GitHub.

By Rafaela C S

Aug 5, 2020

Estudar com essa inteligência artificial falando é IMPOSSÍVEL. E o material escrito só está disponível em inglês. Isso desvalorizou o curso.

By Martin H

Aug 8, 2016

A bit odd this one. It hase some points, but most of the training is looking on what the other courses are.. Like paying for commercial :-)

By 杨燚

Sep 20, 2017

The course was just fine, but I don't think we should spent entire 4 weeks on it. One or two week for this course would be better I think.

By Andrew V

Feb 22, 2016

This course is very basic for a person with an IT background, but nevertheless might come in handy for people without relevant experience.

By Elbert B

Sep 16, 2021

G​ood overview intro, but assignments only measured that you were listening, they did not require applying content to any new challenges.

By Jaume A

Jun 22, 2020

Difficult to follow the robotic voice at a speed of 1,5; the links simply don't workAnd, known bugs on LaTeX need to be found by googling

By Aishwarya K

Jan 25, 2017

There is a slight lack of clarity in videos in terms of audio and also in terms of what exactly the author/lecturer is trying to convey.