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

4.6
stars
32,463 ratings
6,926 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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6176 - 6200 of 6,815 Reviews for The Data Scientist’s Toolbox

By Randy c

Jun 5, 2018

Beginning course in Data Science spent too much time on tools and not enough time on concepts, possible solutions and application. Seems like I spent a lot of time in the weeds of application installation and repositories. humm

By Luis E B P

Feb 7, 2018

I believe that in some of the assingments the student is asked to do a few things that werent taught in the course. And also during one of the quizzes the platform wasn't working propperly, and I had to answere it many times.

By William W

Jun 27, 2018

I don't find the contents about R, git, and GitHub very helpful. They are way too brief and perhaps work better in those specific courses where we have a change to use them. Solely learning some commands is not very effective.

By RAYMUNDO R M

Jul 3, 2020

A pesar de que el curso lo menciona, es demasiado introductorio, no profundiza nada y en mi opinión se pierde mucho tiempo viendo lo de GitHub. Aprendí muy poco de data science, lo demás lo sabía de los cursos de estadística

By Cameron J

Jan 18, 2016

Learned a bit but overall it is literally not worth the price of admission. I think that this course could be offered for free and maybe the others are worth paying for. Hope that the rest of the specialization is worthwhile

By Thomas G

Mar 16, 2021

Automated "reading" of course text aloud wasn't useful to me. Also, I found that the quizzes required research outside of the course which I hadn't expected...I thought the course would be complete and self contained.

By Arnab M

May 26, 2017

Although the course is a good one to get you all set up for the upcoming courses from the Data Science specialization, the content of the course is very less to be considered as a separate course and charged money for.

By chittireddy s r

Mar 8, 2017

Though the course itself is introductory in nature, i wish there was a lecture on what and how exactly are these going to be useful with the help of a real life example and also an increase in the depth of the content.

By Oscar B A

Feb 9, 2016

It is useful to get to know the software that staticians use and some review about them but it doesn't teach you how to use them. A good introductory course for the specialization track but useless as a unique course.

By Shaopeng L

Feb 28, 2016

The overall outline are great. However, the contents and requirements of this course are too simple to be integrated as a whole course. I think 1 lecture should be enough. I am looking forward to deeper introduction.

By Sawyer W

Jun 15, 2017

This course should probably not be it's own course as it can be completed in one afternoon. It might be better suited as the first week of the R-Programming course (to make room maybe move the graphics talk to eda?)

By Deleted A

Apr 5, 2016

The course was fine, but I think it should be offered for free even if someone is doing the data science specialisation track. It is really just teaching you what data science is, and how to install a few programs.

By Chris C

Nov 1, 2018

There has to be a more engaging way of introducing course material. For example, by showing someone actually using these commands in the videos vs. just putting the Git, R commands in a power point bullet format.

By Sergio M

Apr 25, 2017

It's a good introductory course, but it's very basic and I feel that I paid a lot for a very basic experience. I do understand it is the first step in a full specialization but I think it can be more challenging.

By Kanaparthy V N

May 30, 2020

Its always good to have a real teacher's voice rather than an automated. There were also a lot of instances where number of questions were asked even though they weren't taught in the class.

Overall, it was good

By Jeff G

Sep 26, 2016

It is a very basic course to give you high level of what the course is going to cover and the tools that will be used throughout the course. If you have much programming background this course will be a breeze.

By Sebastien M

Sep 4, 2016

Well presented, but this course should be optional in in the specialization. There isn't really enough material to justify it, but it does cover the basics for someone with little to no development experience.

By Ghodratollah A

Mar 13, 2016

With many thanks to the instructors, I expected to learn more. I did not learn as much as a 4-week course in Coursera. Please include more materials and avoid advertising for other topics in the future courses!

By RISHABH G

Jan 21, 2018

The Course is very well designed and anyone who pursues it gets very well acquainted with the applications and tools . But i would like to suggest that this course can be completed in 7 days instead of a month

By Truong T

Jul 19, 2017

The length of the course, in my opinion, is a little bit too long. Actually it took me only 3 days to complete this course and I am not really a brilliant one. So I think maybe may will have the same opinion.

By Dave N

Mar 16, 2017

Not a bad intro; I don't know if anyone would benefit taking this as a standalone (or for an entire 4 weeks, for that matter). Still, it introduced some solid concepts for professionals and scholars, alike.

By PRAMOTH

May 12, 2020

Though the content of the course is nice, i wasn't completely comprehend everything. I was expecting to see a lot of explaining using the live screen mode, i.e., explanation while operating on the desktop.

By mathias b

Aug 15, 2016

This is a really basic course. If you have never touch code before, it's more useful, but little is actually covered here and the gap between it's contents and the next class, R programming is dramatic.

By Chris H

Dec 15, 2016

Super basic, each week was only about 30 minutes of video lecture... but I think that was their goal? Bad form on coursera for making you pay to submit assignments that are autograded to begin with.

By Geoff S

Jul 27, 2016

This is a required course in the Data Science specialization. If you're planning to take that specialization, you should start with this course. If not, you shouldn't bother - there's not much here.