Chevron Left
Back to The Data Scientist’s Toolbox

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

4.6
stars
32,149 ratings
6,869 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.

Filter by:

4876 - 4900 of 6,751 Reviews for The Data Scientist’s Toolbox

By Muqaddas R

Nov 18, 2018

It's a really good course for the absolute beginners, but for me it was quite slow. I just took this course because it is the part of the specialization.

By Ramy H

Jul 30, 2017

There are a lot of info on the video. Would be good to share a copy of the slides for the Git links/instructions so we can use them as a reference later.

By 허욱

Dec 6, 2020

This lecture tells you a lot about new places for experiment and study such as github, r studio. Hope many people check out this lecture and gain a lot!

By Praveen S

Dec 15, 2016

This course provide a good introduction to github , Rstudio and command line interface.

it also gives a information about different ways to analyse data.

By Wai M C

Nov 18, 2017

Basic introduction to the tools that will be adopted in the Data Science. I do hope there would be more information regarding Hadoop, Python, SQL, etc.

By alifiya l w

Aug 1, 2019

As it is a very technical to set everything and to start working on it but the mentor have tried to make it easy. For a beginor it can be challenging.

By Edward C

May 23, 2018

Informative, but course did not provide exact information needed to complete the assignment without additional research (unless that was the purpose).

By Ajay K S

Jul 15, 2017

Although I am vey much satisfied with this course but i felt a little low during the slides for explanation of types of data science .

Rest was superb.

By Jack L

Jan 16, 2017

Pretty light weight so far, but I certainly understand it's targeted at a broad range of people so the vanilla material is probably a chore for some.

By Zhuoxiang Y

Nov 29, 2016

This is a clear introductory course, but the content is not as much as expected. Compared with other coursera course, this one is like one-week pack.

By Harshita D

May 8, 2020

The course is well structured but I still prefer that students new to this must read from other sources as well to completely understand the topics.

By David A

Jul 6, 2017

Good and easy introductory course. Finished it in about 3 hours total - don't expect this to be the pace for the rest of the specialization, though!

By Wissam A

Jan 4, 2017

Lots of information. I learned quite a lot. It was a nice and informative introduction to Data Science in all aspects technically and theoretically.

By Andrés F

Apr 2, 2021

Interesante introducción, quedas con el entorno listo para iniciar el aprendizaje. Se hecha un poco de menos un humano en las clases pero está bien

By Cesar M A T

Aug 1, 2020

This is a mere course on installing all the necessary tools and setting your environment, so the explanations are short lived and practice is null.

By Nicholas E B

Mar 6, 2019

Gives you the basics of how to use R and it's different file sharing platforms, is very useful when completing a project with various contributors

By Graham W

Feb 16, 2016

Good overview, I appreciated that the course gets you set up and makes you prove it. More command line and RStudio simple exercises would be nice.

By PATNAYAKUNI P

Jul 7, 2020

coursers are well explained.some of the topics are not explained .i request you to provide links to study the topics which are briefly explained.

By Emilie B

Nov 15, 2016

I've just started this course, that's why my rating is 4/5. But I'm very satisfied with the video lecture, and I find it very interesting so far.

By Melinda M

Jan 24, 2016

Useful couple of modules for helping you get set up with R and Git/GitHub. Really doesn't require a full month to do.

The quizzes were pointless.

By Tiago O B

Aug 17, 2021

Hands-on, comprehensive course about the basic tools you'll use as a R-based Data Scientist. Robotic narration of the videos is a downer though.

By Tanisha Y

Feb 18, 2021

The explanation of the course is up to the mark. This course is overall good besides you need to follow other courses of the specialization too.

By Anand R

Mar 3, 2020

It was helpful for the beginners who is willing to learn data science and gained a knowledge about Github and other aspects. Thanks for Coursera

By Adam G

Jan 5, 2018

Good course that clearly explains basic R & data science concepts. Workload was very light - didn't get to practice or learn as much as I hoped.

By Bhojraj B

May 4, 2016

This course is great to start with. It provides overview of what is in the course and how should we as students be prepared to learn the course.