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
31,782 ratings
6,767 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.

Filter by:

26 - 50 of 6,629 Reviews for The Data Scientist’s Toolbox

By Annina H

Aug 14, 2019

The course contents are thorough and clear, but the UI and the platform of the web course could use some thought. I find it a bit tricky to take notes and copy url's and command lines from the video. Perhaps this is just a matter of getting use to the platform. Excited to proceed to the next course!

By Anh T N

Jul 24, 2020

Very basic stuff and very dull, monotone computer-synthesized voice. The quizzes are also so easy you may as well not take them.

By Senthil K M

Nov 11, 2016

Impressive explanation on the subject., Freshers with no knowledge about the domain can easily understand the subject. Thank you so much for such a fantastic MOOC mode of learning possibility. Love it all.

By Deleted A

Nov 12, 2017

Really impressed with the completeness of the learning environment. I would rate this more highly than a traditional classroom because of the interaction and opportunity to go over concepts repeadedly.

By Zahscha G

May 25, 2020

I enjoyed the format of this course. It was a good quick introduction to some Data Science concepts, R, and Git. I liked that the same material was available in video/audio as well as reading material.

By Clifton H

Oct 16, 2018

Straightforward and the tasks aligned well with the instruction. Examples were used to good effect. Highly recommend using the course forums if you're stuck on a problem (especially the final project).

By Darky C

Nov 27, 2018

Pretty good in explaining the basics of data science

By Adeyemi O A

Jan 10, 2019

Very good course for beginner in data science

By JEFFERSON D S N

Aug 31, 2018

SIMPLESMENTE SENSACIONAL !

By Maximiliano F M

Aug 12, 2020

Its a basic course to learn general terms of data science. It helps you to set up all the programs that you need to start in this discipline: RStudio, Github and some additional good practices. In general, its a good course. However, I missed coding and a person explaining the videos (i understand the idea behind this, but the concepts on this particular Mooc are so introductory that the argument is not valid for me)

By Usenaliev N

Dec 8, 2018

Would be great to have more reading materials

By Aman U

Jan 5, 2019

Good but need more explanations for topics.

By PALAKOLLU S M

Aug 10, 2018

Teaching of lessons are simply amazing.

By Jasmine P G

Aug 16, 2018

The course is clear and good to learn,

By Md. Z M

May 23, 2020

The course is well structured with enough content provided on each topic. However, the steps to install softwares on Linux, or any instructions to complete the setup on a Linux machine, is missing. Also, I feel that the course is so basic, both in content and duration, that it could be accommodated easily in a few lectures in the next course in the Specialisation. In a nutshell, it doesn't deserve a price tag.

By Lakmini R

Jun 8, 2020

It was basic but was very helpful. However, more things on actual data science should have been included in the course

By S M R R

Jun 11, 2020

Computer voice is not good to listen otherwise the course will be a great material to start data science.

By Yujian B

Jun 10, 2020

Automated videos are difficult to focus.

By S.M.Abid R

Jul 20, 2020

It seems very basic

By ANURAG A

Jun 10, 2020

Robot voice should be replaced by the course instructor's face to face interaction.

By Robert T

Jun 9, 2020

Good course content but I really disliked the robotic voice used in the lecture.

By Adam C

Jul 21, 2020

I started the course but didn't like the computer based audio lectures.

By SHENGNAN Y

Nov 13, 2017

I missed the entire course deadline just because I stuck in one of week 4 projects - pushing a file into GitHub. When I went to the forum, there are so many people in the same situation. The main reason is that the week 4 video did not cover the project content well. Overall, compared to other programming courses I took on Coursera, this course is not well organized at all! Instructors basically just read words in slides, no interesting examples and no hands-on practices, especially week 4 slides that look like a syntax reference document. So the entire instruction is very boring, making me wonder why I need to sit here and listen to word reading rather than buying a textbook. Also, people coming here to learn it are new learners. When the instruction skipped much and made the content not logical and complete, it is very difficult for us to understand what the video is talking about. That's why in forum there are so many people expressing their confusions. This entire specialization is the one that I've taken and feel the worst (I got lost in the R course too). I strongly recommend the instructors of this course watch and learn how the instructor of the specialization "Python for Everyone" organizes and teaches the content. He makes programming become very interesting and easy to understand. He also provides many hand-on practices to help learners understand abstract concepts. Unfortunately this specialization instruction is just about reading words in the boring slides.....

By Maria S

Jan 27, 2021

I did not like this course for many reasons, the primary one being the automated videos. By switching to this type of video, the course misses the mark on the whole point of taking courses versus reading a book -- one of the big parts of learning is the interaction/relationship you form with the instructor and their experiences and expertise. These types of videos feel very cold and detached and are psychologically not effective or engaging. Additionally, there are many mistakes in the section quizzes, and it didn't really feel like the things taught in this course were worthy of an entire course -- they resembled more of a brief intro to the subject and a bunch of reference appendices.

By Christina P

Aug 11, 2020

Although they spend ample time explaining how the course was using technology in order to stay up to date, it was far from it. If you are using a Mac computer, be prepared to google every assignment because the Mac instructions are going to be for an older version. Then I expected to learn about Data Science as a career... not in this class. I feel like I know no more about Data Science than I did when I began. I am probably not going to continue through the entire certificate, and instead learn the languages it suggested were more common - SQL and Python, and pick up the "Data Science" somewhere along the way.