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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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4876 - 4900 of 7,122 Reviews for The Data Scientist’s Toolbox

By Jackson B

Apr 9, 2020

Overall, wonderful course - but I would request that you change the signature name on the certificate from "John Doe" to a real professor's name. Having John Doe on the certificate makes it feel inane - I would never show this to somebody with whom I was applying for a job, for example. Other than that, loved the course. No issues.

By Jim L

Oct 5, 2021

I have decades of experience in the field, and am using this to broaden from SAS to R. Much of this was a review (as I knew some R already), but overall I was pleased with the course. Some of the quiz questions were more trivia than what I would call actual knowledge, but those items were inconsequential. A decent introduction.

By MOHAMAD A

Sep 29, 2020

Great course. The only gripe I have with it, is that sometimes the same question is asked during the tests after each module. Also, I got a lower grade because only 2 people graded my work and 1 made an error. I did get half of the points as they averaged, but still. This however is with Coursera I imagine. Definitely recommended!

By Robert S

Jun 10, 2019

If i could redo this course, I would have taken it simultaneously with the introduction to R course. On it's own it feels like a grab bag of information and it felt like I was delaying getting into the meat of things. That said, the information itself is very important and I found myself referring back to the lecture notes often.

By Paulo C M

Oct 31, 2016

Good introduction to basics. A few improvements are warranted:

Lessons could be reordered in a more logical progression, particularly when it comes to Git.

Gitbash is not easy or intuitive. A more structured approach (e.g. with cheat sheets, command glossaries, structure diagrams, debugging algorithms etc) would help assimilate it.

By Luiz F

May 22, 2016

The course is excelent for people who don't know anything about R, Rstudio, RmarkDown, Git, GiHub and other tools. However, for people who already know a little bit of those technologies, they will find it a little repetitive. Anyhow, the classes are awesome for you to get to learn to use those tools. Congratulations to the team.

By UJWAL S S

May 29, 2020

Automated lecture are made using difficult english to understand, it feels like that robot keeps speaking continously without a stop and also the presentations in the videos makes me feel sleepy, if you use facecam that would be better for the learners but not for you i understand that. This course is little far from perfection.

By Sandra V

Sep 21, 2020

The content was clear and easy the first three weeks. But it was confused to me at 4h week and for the final presentation it was a lack of clear instructions, I was so sad because I had many troubles at the moment of commit, push and fork a file, I had to find external help and I thought I couldn't finish succesful the course

By JAVIER D L R A

May 21, 2020

Excellent Course, very simple to understand and concisius. If you wish to learn data science and you dont have any idea about it this this is your course. Only the part of Git I wouldl like to be more explicit, because in one part there is not very clear how we have to create a text file with extension .md using Github. Thanks

By Ross B

Feb 10, 2020

Course was pretty good but the later lecture videos go really fast and are hard to keep up with. The main problem I had was when it covered R markdown it made no mention of having a LaTex program to create the pdf, I had to spend some time figuring out how to install and get one working in order to knit the markdown file.

By Jeff M

Oct 6, 2017

What needs to be made clearer is the need to go looking around the internet for help on the Git to Github work. I can see that one taking some time for students to work thru. On the other hand once students go throw the trouble of doing the research and working with the code/commands a strange thing happens - learning!!

By Miranda C

Aug 28, 2023

A little out of date, wouldnt be a problem except it made some parts a little harder to figure out. Google was definitely a friend here.

Learning how to do Markdowns could have a little more matter on the subject and more assignments on getting started with it, again, can be supplemented with google. Still a great course!

By Steve

Feb 1, 2021

Nice, basic introduction to setting up RStudio and Github. I think the idea of using automated lectures is okay EXCEPT that there is no control of pacing. The automated speaker talks far too quickly when explaining steps that we need to follow on our computer. I found myself constantly pausing, rewinding, and replaying.

By Cesar A d S P G

Aug 14, 2016

Expectations for simply meeting the baseline learning objectives or to outpoint it aren't exactly clear and there are two monitor strings that are far from being clear (15 minute guide on xyz).

Content and evaluations match in requirements. I learned a lot about softwares and databases in with which I can learn and work.

By Chinmoy C P

Mar 8, 2020

A high level view but very helpful for someone starting their Data Science journey. Good overall coverage of basics that helps in building a gradual understanding of the subject.

The only reason i haven't rated 5 stars is because there were lot of errors that i came across in the automated diction that need correction.

By Muneeb S

Feb 15, 2020

Organization of course was good. Sometimes, I felt that speed of the lecture is fast and I had to reduce the speed to 0.75% to understand important concepts. Improvements can be made in the transalation of text by robot, 'e-g' was being translated to EG instead of for example. Overall the content of the course was good

By Xuan L

Jan 13, 2016

A brief introduction and overview of data science and the specialization from JHU. It provides necessary information and materials for the following courses, but itself does not cover much technique details. Won't take long to accomplish but still necessary if you don't know Git, Github or background of data science.

By Jan-Frieder H

May 12, 2018

very basic when you have at least some science background in terms of a Bachelor + almost Master Sc. degree, but good for repetition, Git Bash and Github was completely new to me, at the moment I am not 100% sure for what Github and Git Bash are useful, but I am sure I will figure it out in the upcoming courses :)

By Vignesh v

Jun 26, 2020

It was good and it helped me to explore github,git,R and Rstudio. The peer assignment was quite good as it was my first peer assignment..But,only thing is that instead of this format(using AI),U can use on-person teaching which will be good and interactive..

I felt sleepy with the crampy female robotic voice

By Kendra S

Feb 15, 2021

The peer review is very subjective. The last question on the grading rubric is about whether or not the work was done by the student who submitted the assignment. One person said yes and another said no, so I only got half a point. I would have had 100% if not for this. I can prove that the work is my own.

By Deleted A

Jul 22, 2020

Found that the automated lecture didn’t deliver the message as well as a traditional lecture. There was awkward delivery in terms of speech and phrasing from the automated lecture and I found it distracting. But the material was great and I feel prepared to start the rest of the data science specialization

By Harris W

Apr 29, 2020

The course overall has been helpful in getting started with R and data science as a method of analysis. But the robot voice is extremely difficult to listen to. To the point where I am drifting off because it is so monotone, and sometimes not interpreting the content correctly due to a weird pronunciation.

By Matheus d M d A

Aug 28, 2018

The course is pretty interesting, but there is not much substantive knowledge here. For that you must keep going to the other courses of the Specialization such as R Programming and the others. There you are going to learn data science in practice. Nevertheless, this is a good introduction to the topic.

By ANEETA B K A

Oct 15, 2022

The course helps me understand more about data science. However, I see that when instructing using an automated voice, the way the course was taught was kind of boring. I took longer time to digest and complete this course. Hope that in future to variate the voice, not just specific to one voice tone.

By Ian M

Apr 1, 2017

Good course, that brings goos insights on the basics about data science.

The lectures about Git and GitHub are not so clear - maybe this classes would better fit when the class already have a more advanced knowldge on the course's theme.

Thank you for the quality of the lessons and to make it available.