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

4.6
stars
33,156 ratings

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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6501 - 6525 of 6,981 Reviews for The Data Scientist’s Toolbox

By Nikita S

Feb 2, 2018

I don't really think that this amount of information should exist as a whole separate course.

By Lucio C

Aug 8, 2016

Good overview. But it is confusing for the first class when you have no idea about the topic.

By Bhupen P

Jul 22, 2021

Need more practice in R programing, Github, commit, branching, adding text, making directory

By Maciej M

Feb 18, 2018

some information was interesting but in general I don't think it was crucial for learning R.

By Benny B E

Aug 1, 2017

If you don't know any thing about data science, good introduction, otherwise a wast of time.

By Yves-André G

May 27, 2017

A very simple course, focussed on installing the correct tools on your computer to learn R.

By Migdonio G

Feb 11, 2017

Too little material for 4 weeks. All this could've been written in a PDF instead of videos.

By Mark P

Oct 11, 2020

the computer voice is very hard to handle.

low production value of the course in that part.

By Kapeesh

Jul 26, 2020

Video lectures where TTS, not at all engaging. Thankfully, text material was well written.

By Shahrooz

Jul 22, 2016

Overall the course content is good, but the power points are not engaging and interactive.

By Mantra B

Jun 27, 2020

Very Basic level. A little difficult to stay focused without having an instructor around.

By Sadanand U

Aug 19, 2018

Very basic, may be a bit more use cases on Git would have been useful. But that's just me

By Uian S

Nov 23, 2017

Few content for an entire course. I think this one could be together with R Programming.

By Ali A F A N

Apr 12, 2020

Wasn't as good as I expected, but still I learnt from it, I can say it's above average.

By Andreas L

Dec 3, 2017

I am aware that this is the introduction to this topic but it was a bit long-drawn-out.

By Juan J E

Oct 22, 2017

I was already familiar with some content. it was a good starting point for may training

By Craig G

Jan 27, 2017

A good intro to the tools, but for anyone with prior programming experience unnecessary

By Debanjan D

May 25, 2019

Okayish course. This course will give you an introduction in RStudio and Data Science.

By João P S

Sep 7, 2017

Too few activities for the time allocated. I completed this course in 4 periods of 2h.

By Danyal F B

Jun 7, 2017

I think the project became very confusing since no examples were done in the lectures!

By Seckin D

May 20, 2016

I think this class is best for academic people. I did not find what i was looking for.

By kheman g

Aug 5, 2020

This is a very basic of the course where I learned so much about the different tools.

By John Y

Jul 8, 2017

This could be wrapped into one of the other courses since its just environment setup.

By Ryan C G

Jan 17, 2017

Pretty simple, the Univ of Michigan Data Science with Python set the bar pretty high.

By Ankush K

May 31, 2017

A little boring. Necessary if you have ABSOLUTELY no experience with data analysis.