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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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4901 - 4925 of 7,122 Reviews for The Data Scientist’s Toolbox

By Antony S

Apr 28, 2017

A good place to start of your entry to Data Science. You get to know what data science is, what are the tools used and get an idea of what can be done and cannot be done. The course even walks you through installation of r, rstudio, and git. It introduces version control system using Github too.

By Dawn K

Mar 3, 2020

I really wish there were a few videos with real people in them. That computer voice is annoying, but the material was covered thoroughly, and I used the text option which actually was great. I also think it would benefit students if there was a book or some form of notes they could download.

By sachin s

Dec 26, 2019

A Good introduction to data analysis theory and tutorials on getting started with Rstudio and git installation and initial usage techniques. Consecutive course to compliment this would be R programming and Data cleansing and exploratory analysis as in John Hopkins Data Science Specialization

By Syed M R A

Jun 1, 2017

Very good stuff relating to Data scientist's entrance in the Data Science field but it should be more descriptive in terms of basic tools and softwares like git and github. Although the stuff is available over the internet but when you listen & see, you get more and more efficiently. Thanks,

By Marco L

Feb 5, 2017

It was a little to easy and the quizzes were not really necessary. Questions like "What courses are in the Data-Science Specialization?" don't help to controll my learning progress. However for a first, introducing course it was okay. R Programming is way more interesting and challenging <3

By Ziaur R

Dec 20, 2019

Didnt enjoy the voice on the automated videos, but was faster at reading than watching videos. The document didnt work for the Big data Section and had to watch the video for this. Good introduction and wished I had more questions to practice! Looking forward to R Programming section next"

By Glauco G d A

Jan 11, 2018

It's a good start point for people who wants to start pursuing a data science career and haven't a statistical background. Explain the basic definitions of research analysis types and shows the very beginning of handful tools like how a git repository works and good editors for R scripts.

By Emma G

Aug 22, 2023

The course was good except for the updates that it needs. To link Github and RStudio, you need to create a personal access token on Github and use that as the password when it is prompted on RStudio. There is no mention of personal access tokens in the course so that needs to be updated.

By Marek B

Mar 11, 2018

The course is very basic but still contains useful information both on data science and some of the tools.

Unfortunately, because of how basic it is, I found the quizes focusing on trivial and subjective questions that are both hard to answer and not really testing any interesting skills.

By Muhammed A A

Jun 24, 2021

i think is good course they explain to you Data science and all things about it and how to install and use the tools of data i think the problem is the robot that they used as speaker i think the voice of human better than robot for me and the translation for Arabic isnt really good .

By Bernard O

Jan 10, 2022

One would need to do some additional hard research in between though to complete the course due to the automated video which skips a couple of steps including the discussion on the Git! Hope this will not be the case on the rest of the courses. overall Good course but 5 stars for me.

By Candice A M J

Jan 24, 2020

The tools needed are all explained well, including installation. Still getting used to the new Amazon Polly format. A few questions in quizzes seem to not align with updated material, but that could just be an intentional push to be resourceful. Looking forward to the next course.

By Sarah G

Sep 6, 2017

Overall a really nice course for looking into Data Science. I would've liked more on the general field of what is data science and what kinds of problems you might solve, etc. But the lectures were good and the timing was very manageable for working professionals to do. Thank you!

By Lebogang M

Mar 7, 2021

This course was amazing, mostly teaches how to manage your work as a Data Scientist. Essentially it's is a great course to take if you feel like you have no idea on how data science workspace is managed. I found GitHub to be a very useful tool! I will defs be using it in the future.

By Alberto H A

May 19, 2016

I found this course to have very useful material and good, clear explanations. My only criticism is that the last of the four weeks has practically no content. There are no lectures and the only assignment is grading the assignments of other students, which at most takes 20 minutes.

By Lee K

Jun 29, 2020

The part on how GitHub works (Including the Git Bash) section could be further discussed for a better understanding of how to use the platform. Overall it's a good course! well structure. just that content could be more detailed so that it will be a even more meaningful course :)

By Figo C

Dec 3, 2017

Great learning on the basics of Data Science and it's importance in real-world applications. Help to get started with introduction to Python, R Language, Git!

Lectures could perhaps be more engaging and have more visual appeals (instead of having just lots of words on most slides)

By RAVI M

Jul 26, 2022

This a beautifully desined course to introduce someone completely beginner in the field of Data Science. But i gave 4 star because there should be more description of the things like R Markdown, git, github etc. Also there should be more tools included not enough tools included.

By Guilherme B D J

Feb 16, 2016

This course is good to get all your programs set up before you start your studies in Data Science.

I think it could offer a little bit deeper knowledge of git and github in order to guarantee it will not be a problem later, since they will not be strictly related to data science.

By Eugenia G

Jan 22, 2016

The course content is very useful, but explanations are short and It's unclear how to install R studio for the Windows (I found it at Youtube). Also I had a problem how to install the R packages, and solution was simple: you should run it as administrator (it wasn't in lecture).

By bt19103033 R J

Sep 25, 2020

This course is the beginner course , in which you will learn about the basics and get to know the tools you need to develop your career in DATA SCIENCE field. This was the optimal course to get you familiar with what basically is data science. You only need a question ..... :)

By Ximena R

Mar 31, 2020

I felt like I was able to keep up with the course material fairly well. My only critique would be when it comes to using git, the commands aren't very intuitive to me. Maybe explaining the commands a bit more would be more helpful, i.e. what the commands are telling git to do.

By Rahul P

Jan 24, 2017

Very nice introduction! Unlike a lot of online courses, this course is no fluff or jargon. It is solid stuff with hands on experience. I only wished this course was longer. After completing the 10-week Machine Learning course by Andrew Ng, this course felt a bit too short. :-)

By Valentin Q

Feb 21, 2022

The course is interesting ... however, the teaching is very minimalistic in terms of visualizations and explanations. I would prefer a real teacher - however with the electronic voice and some more and better designed ppt slides you could achieve better results ! Stay on ;-)