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

4.6
stars
33,829 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

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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4951 - 4975 of 7,122 Reviews for The Data Scientist’s Toolbox

By Steve S

May 8, 2016

Good pace for the first course. A little more guidance on Git command flow would be help. However, the available Help documentation on Github did the trick. The problem was having to work primarily in the command line which provides limited feedback.

By Grace H

Sep 24, 2023

This course has good content, but the instructor's voice is all done by AI. They explained early in the course that this is because it makes it easy to make changes to the videos, but it still creates a depersonalized learning experience for the viewer.

By Francesco B

Jun 10, 2019

Well done, but very basic. Only do it if you are really completely new to the subject.

The audio part is entirely done using automatic text reading. Very well done compared to other similar tools, but still the experience is not the same as with a human

By Natalia S

Sep 7, 2017

Videos are already sort of "old". Having Macbook i had significant problems with pushing files to GitHub repo, nevertheless I was doing everything said in the videos.

I could do that after using some other functions that were not mentioned in the video.

By leo n

Apr 21, 2019

It was straight forward. However, there were some difficulties installing RStudio using the latest version. I had to go the previous one .e.g. Latest was 3.5 I used 3.4 matching RTools. Other than that very straight fwd, including Github (basic) usage

By SRI V K

Jun 9, 2021

I am not too thrilled about Polly delivering the lectures but I understand why they have to do it this way.. Still explained all the concepts clearly and I am confident that I will get through the entire specialization after going through this course.

By Scott D

May 7, 2020

A good course with clear instruction that gives you a basic review of using data and installing R and related programs. Occasionally necessary steps in R are omitted and one has to do some googling. Not a fatal flaw, but frustrating for a beginner.

By Roberto R

Jul 23, 2020

It felt a bit like a RPG tutorial where your big accomplishment is learning how to run or crouch, but I guess it makes sense for it to be part of the Specialization track. I would recommend it as part of a series, more than as a standalone course.

By Carolyn A

Feb 8, 2016

Great introduction to the different tools that a data scientist will encounter and use, including RStudio, Git, and GitHub. I would have appreciated more practical experience linking Git and GitHub, as that is critical for version control of code.

By RICARDO F F D L J

Aug 6, 2020

I liked the course. I think that at times it is not clear and at others it is wordy. I gave 4 stars mainly because the course menu promises subtitles in Portuguese and in more than 60% of the videos there are only subtitles in Korean and English.

By Samuel M A

Apr 5, 2020

I had some issues in following all the steps that are shown in the lessons. I think the demos skip important steps. But, on the other hand, it forces to search and look for solutions to these issues on the web. Overall: good introductory course!

By Jeroen v B

Sep 12, 2016

It's a good course, you're not going in-depth but this is just an introductory course for the Data Science master and the tools you will use. You will learn the basics of Git and get acquainted with R and is thus somewhat essential for starters.

By Wendell B

Mar 19, 2020

Reviews or Test should rely more heavily on the instruction that goes into detail on a topic matter and questions that were asked on quizes. For example, the datasharing question was worth 2 points, when that topic was only cover very briefly.

By Reinier B

Feb 5, 2018

Although I found the course material in general clear and well-explained, I found the lecture on 'Basic Git Commands' poorly explained and sometimes poorly audible as well. For a non-native speaker of the English language it was hard to follow.

By Shashank S

Oct 29, 2016

This is a good course for someone who is not familiar with the basics of Git,Github and needs to install R,Rstudio and related packages. If you are not the kind of person described above you will be able to breeze through the course very fast.

By Azin S

Nov 21, 2017

The course is very fluent and attractive. You may run into some questions while following the course which you can easily find the answer to by googling it. As a beginner in both Data Science and programming, I'm very happy with this course.

By Sarwar A

Jan 20, 2020

The lectures were good.After all it's robot orienting converstaion it has lot of pace in speech I think that is not good for me.Because It was little bit hard to grasp the message.The pace is only the concerned.Overall lectures were good.

By Kevin J Y

Sep 10, 2017

There are some typographical errors in the quizzes and the english subtitles. Not really a big deal. The Week 2 about GitBash made me a little confused because the video about loading git bash happened before the video about installing it.

By Daniel A (

Sep 11, 2020

I am giving the course 4 stars because it is online. should it be practical, then it would have earned 5 stars. Some of the concepts were unclear especially "Experimental Designs". Hope there will be more practical examples to work with.

By Kayla d V

Jul 3, 2021

Buen curso, informativo, completo y bien explicado. Buena guia para empezar con Data Science. Me hubiera gustado que incluyan mas ejemplos practicos para poder entender de forma integral cómo vamos a aplicar estas herramientas a futuro.

By Muhammad A K

Jun 8, 2021

Overall the course was well presented, and I learnt what I was looking for. The only thing I would suggest is to improve the project submission. In fact the process for submitting the project work was not explained before it was taken.

By tierny a c

Jul 22, 2018

I don't feel as though the 16 minute video on command lines was efficient. I spent a gross amount of time (over 3 hours) on youtube for supplemental instruction just to complete the final project. Otherwise, this course was sufficient.

By Victor A T

Jan 26, 2020

A very good course for beginner to start off with. This course really helps setup the fundamental toolkit to create a efficient workflow. The git/github version control linking with R/Rstudio is the best thing I got from this caourse.

By morgana

May 24, 2017

Excelent course. The schedule was basic however have approached a thematic complex and important.

The time to complete the tasks week was great.

But I felt need to learn more about git and github. I don't know if it was on follow weeks.

By Marc S

Feb 24, 2016

Easy to follow. Might be too easy for some people with experience in data analysis. However, the instructors also talk about some frameworks and insights from their experience which could be helpful for even those who have experience.