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

4.6
stars
31,931 ratings
6,810 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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126 - 150 of 6,683 Reviews for The Data Scientist’s Toolbox

By Filip B

Mar 11, 2016

This course is (as stated) suitable for beginners on the subject. It gives a very good introduction to it, and helps people learn more about what the data science is all about, how it works and which tools are usedby data scientists.

This course helped me to determine if the path I was thinking of taking as a career options is really interesting for me at this point.

By Primadina H

May 30, 2020

Firstly, this course was challanging for me, especially to understand linking github in R. I have known R, however I never use git or github before. I have stucked for little moment to understand about it and missed my deadline. It was because I'd need some times to understand and elaborate it. And now, I can passed the course, and I'am happy. Thank you Coursera.

By Rayne K

Jan 27, 2016

So far this course is given at a pace that is just perfect. The instructors explain concepts in ways that make the subject matter easy to learn, particularly for someone who loves data, but is terrified of heavy mathematical concepts. I've taken similar courses at local community colleges where class size is much smaller, and have been very disappointed. So f

By Benjamin T

Aug 10, 2020

Muy clara la explicación de las herramientas. Lo mejor es la introducción que se le da a herramientas como github para poder crear tus propios proyectos. Defitivamente es muy útil para los que no tenían ni idea de como ingresar a estas plataformas. El curso se puede terminar en 3 o 4 dias facilmente usando un par de horas por día. Gracias al equipo.

By Edmund J L O

May 11, 2016

This course gives a wonderful introduction to the world of data science. You'l probably finish it with plenty of time to spare which makes jumping in the middle of the next course very tempting. I did that and i had a hard time. It would be best to familiarize yourself with the other commands in github and explore the many helpful sites instead.

By Indrajeet M

Jul 25, 2021

Data science has emerged as one of the most important pillars in today's competitive environment. It is vital to educate yourself on the subject. Coursera is a fantastic resource for anyone who wants to learn something new, quick and easi manner. Coursera offers a variety of courses that everyone should take advantage of. Thank you, Coursera team.

By Atul

Oct 20, 2020

As I want to become a Data scientist and I enrolled in this course this course is amazing teaches allot of thing. As when I enrolled in this course they taught me from the basics. In my past 2-3 years I was not knowing about Rstudio, R-programming etc. But coursera taught everything from basic. Now I fell that I have enrolled in the right course

By Igors K

Mar 12, 2019

good tool tips but with some hard to make SSH and pull not working downloaded github desktop and take projects from RStudio and pull, using github desktop maybe add some tips for this program because to some person it will help like me, every have diferent PC and language.(Searched google every writing about some space not about solving problem)

By chitradeep g

May 16, 2017

I would like to thank Coursera team for providing such a good opportunity specifically the mentors of JHU, for sharing excellent video lectures. I would recommend my friends, colleagues, and juniors about this course, who is having keen interest to grow into the field of data science. Looking forward to complete the upcoming series of sessions.

By Vanessa K

Sep 9, 2020

This was a great beginner course given that I had no previous experience with coding or R Programming. It went at a good pace, I could work on my own time, and I appreciated the option for both video and script. While it only taught basics, it provided websites and connections needed to continue my understanding of the data science community.

By Rolands Š

Apr 18, 2020

Course is not as time-intensive, however it contains a lot of important information and helps lay out solid foundation in data science. Information is presented in an easily digestible and engaging manner, including some fun references/easter eggs that help lighten the mood. Tutorials for software are also easy to follow. Highly recommended.

By Theresa B

Aug 11, 2018

I really loved the presentation style. It cratered to all learning styles which I find to be essential for online coursework. The information was basic, but it never hurts to have a solid foundation before going to the next level. Since the next course really throws learners into the deep-end, this course is necessary to be ready to go.

By Dr S D S

Apr 23, 2021

Its a good Course. The Questions and Assignment were framed well to make us think. Although I do feel much more questions should be added to properly assess the level of expertise achieved from the course. Then you would also be able to grade the level of expertise achieved and this would help in stratifying students as per their needs.

By MASROAF S S

Sep 4, 2020

This course is a kickstart to the further R-programming related courses. Those who want to learn R programming with strong basic on its background, then this course is the right choice. The course materials are too much easy to complete but easy to those who attentively listen to the lecture videos. Heading towards the next course now!

By Pavel T

May 15, 2017

That was introduction to Data Science specialization. Not too valuable as independent cource, but basic for whole specialization. Speaker briefly informs us about purposes and specific of data scientist job, indicates common mistakes and review tools for data analisys. Narrator is pleasant, seems like he is professional in this field.

By Scott C

Apr 5, 2016

This course is a good, brief introduction to the foundational concepts of data science and some of the tools you can expect to use when doing data analysis with the R programming language. It's best suited to someone who intends to continue at least with the R Programming course that is also a part of this Data Science Specialization.

By Randal N

Jan 2, 2018

Great introduction to data science and the associated tools. As someone new to data science this course provided a simple, yet firm and comprehensive foundation for the rest of the courses in the data science specialization. Definitely worth doing this course if you are thinking of pursuing any endeavors in the field of data science.

By Jonas H C W

Aug 21, 2020

I thought this was a very fun experience. It was easy to follow along and it didn't take up too much of my time to pick up some interesting concepts. Though I do recommend that you watch some videos on YouTube with explanations on Git and GitHub, because that will really help make version control systems so much more understandable!

By Yanal K

Jan 7, 2016

First experience got me hooked. I love coursera. This course, even though an introduction taught me a lot and showed me an error of my ways in everyday life. One question in the 3rd Quiz was very confusing to answer. But that's about it. I hope the rest of the specialization carries on forward in a similar maybe even better pattern.

By Sandhya M

Dec 29, 2019

The course was completely new to me. But the step by step instructiona made it easy for me to complete the course succefully. Linking of R and GitHub is like a magic to me ,who is new to programming. The Video on Control Version is fantastic and can be helpful for even professors like me who give group projects to their students.

By xi l

Nov 19, 2017

I think this course did gave me a full impression regarding data science and guided me how to install basic tools successfully. Also, I found that the help guide and links those are introduced during lecture are very helpful, such as "Github help" and discussion forum. I used them a lot when finishing the last peer view project.

By Daryl B

Jul 31, 2020

This was an excellent course. I always wanted to know how to use GitHub and this course knocked it out of the park for that. Also learned how to set up R & Rstudio on Debian 10 vs. Windows and/or Mac. I'm a FOSS guy so this course provided sufficient guidance around how to build my Data Scientist toolbox on that platform. Nice!

By Egor M

Jul 23, 2020

A short introduction to the primary tools and concepts for data analysis with R. The lectures cover a fair range of topics from installing the software to experiment design and types of data analysis. Relevant and informative examples are provided for each section. All in all, the course is a wonderful introductory experience.

By SZE P L

Jun 6, 2021

This is a great course to startup a Data Scientist journey. Learn how to setup the tools to be ready for R programming and the concept of data analysis. A minor negative comment is that the robot voice is really annoying sometimes, but it is well explained in the Welcome notes and videos. OVERALL, good course to be enrolled.

By Lucho B

Oct 31, 2020

It was interesting, including the presentation itself in the sense of the automation of the generation of the course. I will probably copy that idea for my future courses, otherwise the content without major problems. It catches my attention that they do not explain or at least indicate how to install these tools with Linux.