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

4.6
stars
32,455 ratings
6,924 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

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.

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.

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6251 - 6275 of 6,813 Reviews for The Data Scientist’s Toolbox

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.

By Raneem Y

Jun 29, 2020

thank you for the course it was useful. However the machine voice is really annoying and make fell uncomfortable and unfocused all time

By Siyang N

Dec 5, 2020

Course content meets the standard. However, the computer voice is really terrible. I suggest you switch back to human voice teaching.

By C. M B

Sep 7, 2017

It's a very basic course and easy to get through. I wish that they wouldn't make you wait to get to the next section of this series.

By Oliver K

Oct 19, 2016

Gives a good overview of topics and the specialisation, however is still very basic. I'm looking forward to the next advanced courses

By Matt S

May 14, 2020

Some of the information for this course seemed to be missing and I felt I had to either guess a lot or search the internet for help.

By Alejandro S J

May 17, 2016

Good as just an introduction to data science. Some more exercises using Github, maybe some collaborative works would have been nice.

By Pedro H C C d A

May 21, 2020

The "robot voice" speaks really fast making me having trouble to understand the content several times. Overall it's a great course.

By Ioannis V

Dec 31, 2017

gives some good information but the git section isn't really well made and it could have some improvements on sound and quality

By Brandon D

Feb 16, 2017

Very basic overview of the tools and installation of them. Should be an optional course rather than part of the specialization.

By Baktygul A

Jul 9, 2020

Peer-review assignment questions leave out some assumptions; it took me a while to figure out what exactly was expected of me.

By Anmol A

Jun 25, 2018

This course was a beginner level course and the difficulty level was quite low and in depth detail should have been provided.

By David R

Sep 4, 2017

Extremely basic, should likely be a pre-req for non CS/IT types but could easily be summarized for more experienced students.

By Lluís G

Sep 2, 2016

It is a good introductory course, but it could be optional for people with some experience in the field, as it is very basic.

By Alberto G M

Feb 8, 2016

The real basics of data analysis. The course is not bad I would just say it may be too simple even for an introductory course

By Rajeev J

Sep 15, 2018

Didn't get an awful lot from this course. The videos have a lot of information which are not directly related to the course.

By Bob D

Feb 5, 2016

This is a good introductory course to some of the tools but it doesn't go into the details of R programming or Data Science.

By Чмуров М В

Sep 21, 2019

не представляет ценности в качестве отдельного от специализации курса. весь курс является просто введением по специализации