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

4.6
stars
31,793 ratings
6,772 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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6376 - 6400 of 6,631 Reviews for The Data Scientist’s Toolbox

By Atul K

Jan 31, 2018

Motivating

By Paulina B

Jul 17, 2017

Very basic

By LIAO J

Jun 12, 2017

very basic

By Xin T

Jul 23, 2019

Quit easy

By Diqing F

May 8, 2017

Too easy.

By Harsh V S

Mar 27, 2017

too basic

By Le C V

Apr 22, 2020

Thanks !

By Ilija P

Jun 26, 2017

To easy.

By Justin z

Apr 13, 2017

too easy

By Hernán S

Feb 29, 2016

Too easy

By Raúl M F

Jan 11, 2021

Easy

By Umesh K P

Jun 1, 2020

nice

By Meenakshi D

Dec 18, 2019

good

By Kevin C

Jul 14, 2016

good

By Haciyev M

Aug 31, 2020

ok

By José A G R

Jan 10, 2017

ok

By Mauro C V

Jul 3, 2020

I

By John M

Jan 11, 2016

B

By Todd H

Jul 15, 2018

I am simultaneously doing a course here and one on Udacity. In comparison, this course is much less enjoyable and efficient. There are several reasons for this 1) you never see a person present the material in the videos, it is just pictures of slides. This makes it feel less personal and enjoyable. 2) The lessons are relatively long and there are not opportunities to practice in between. Udacity, for example, has short 1-2 minute videos for each concept and then ungraded practice quizzes, which make it very clear what you are supposed to learn without feeling like you failed if you make mistakes. This saves you time so you don't have to go back into a 15 minute video to hunt for an answer to something. 3) The quizzes here test a lot of minutae. They are not always focused on the main points from the lecture. This can be frustrating because you may feel like you need to spend an unreasonable amount of time looking for answers to small points or get frustrated and feel like you are failing. That does not really make sense for an overview course. 4) The instructor often rambles or has side remarks. He sometimes forgets to give the proper background information for beginners. Takeaways or action points are not always clear. 5) This course feels unnecessarily long for what it is supposed to accomplish. It could be a list of programs to download and a very short summary of things you will learn in upcoming courses. Instead, you spend hours on this and feel like you walk away with no new technical skills.

By Chloe B

Aug 29, 2016

The course is fine, however its more an introduction than a course. The course in itself doesn't teach much, should have been the first week of subsequent courses. I went through all 4 weeks in 1 week, the whole course is mostly about downloading different tools and signing up for accounts.

What I didn't like is that the teachers seem to be really concerned about their reputation and workload. Its repeated several times that you shouldn't email the teachers with questions and that online questions should be of a certain standard, its understandable but its a bit patronizing. I think teachers should be available for questions, even if its only through the forum (which they are) Its understandable that there are a lot of students so direct emails might overwhelm but that's just part of the job, we pay for the course, we should also get support when its not working for us.

Overall I wouldn't advise taking this course if you aren't taking it as part of the specialization.

By Shawn L

Feb 18, 2016

I think this course could have been done in two 30 minute videos. It jumps in with overviews but contain some high level items you won't understand until later in the course and it really doesn't give enough context to be meaningful at the time. It almost seems like it was thrown together without a clear mission of what should be in the introduction. Being a developer who has used some of the tools in this toolbox (Git, GitHub, Command Line) this intro really glosses over tools that most non developers won't understand. If I had a say in what should be in this intro it would be one video end to end of setting up the tools. The second video would be all about the history and logic and some of the applications we will be exploring without all the r formulas in the slides.

By Susan C

Dec 26, 2020

The automated voiceover is really unpleasant, it's like listening to a phone menu over and over again. If you choose not to listen to the voiceover, it's like reading a book, so one might as well buy a good book or read through some documentation on the web.

My other problem with the course is that it contains a fair amount of subjective information. For example, the quiz might have a question like 'What are the most important characteristics of a data scientist'. Well, the answer to that is obviously subjective, and other data scientists might have a different list.

That said, on the plus side it worked as a quick introduction to the R toolbox, the R/git connection options, and R markdown, all of which were very useful.

By Florence C

Nov 8, 2018

I wonder if most of students who took this course would have expected to keep installing software, one after one, and seems never end. For the whole week course, there is nothing related to the course. The worst part is that once I got into trouble to get a software work, I got stuck. I spent hours and hours to search for a solution on the web. However, most of the answers are too technical for me to understand. Although I understand that data scientists have to use some computer programs to assist them to the work done, I don't think that, as a novice, at this stage I need anything like GitHub or git to help me learn the subject. Moreover, I'm not sure if I would be taking another data science course yet.

By Cándido O M

Oct 2, 2017

Too basic material. I had to watch everything x2 faster to keep my attention. This course is just an overview of the topics that will be explained in the next courses, which could be much shorter in just one lesson or just avoid it. It is only useful to have R and RStudio installed and to introduce you to GitHub if you do not already know it.

I think it would be an improvement if you made the videos longer in order not to repeat yourself. Because sometimes you are constantly reintroducing a topic and never getting to explain much of it.

I hope that the rest of the courses be more direct and easier to keep my attention on, because I really what to learn about this subject!

Thank you

By Julia S

Mar 1, 2017

This is really bad structured. As analogy - imagine a cookbook that says: in chapter 8 you'll learn how to cook pies, but here in introduction let me tell you how to add baking powder in them. It is not useless information it is just very out of place.

Learning some git commands was the most usefull in the course for me. (Though again, why would you first show the commands and just after that explain what's the tool for and where to download it?)

And by the way it takes half a day to cover all 4 weeks material (listened through all videos, installed the tools). Which is not bad, just of other users information)