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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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4801 - 4825 of 7,122 Reviews for The Data Scientist’s Toolbox

By Robert L

Oct 11, 2020

Very basic, but quick to move through course with the minimal needed to setup RStudio and connect with github. I am super familiar with source code management. I haven't used R but the environment was very simple to setup with the instructions given.

I actually did enjoy the general overviews. The first week I didn't bother taking notes but enjoyed. The fourth week I actually got some solid overview information out of and took good notes.

4 stars for the automated lectures. Not bad, but I was SUPER relieved that the next course did not have these. I may have ended my trial. It was definitely minimal, but better than a bunch of useless extra information added in.

By Vanessa M M

Dec 24, 2019

It was really good for a beginner's course. I thought that knowing how to code was the only limiting factor when it comes to learning R but this course showed me that as an upcoming Data Scientist, one needs to know what they want to do in R and decide how they want those questions answered. I got to learn far more about Git, Github and R Markdown which I think will really be helpful for the projects that I will set up during my PhD. The course was 4 weeks but I managed to get through it in 3 days. I am especially happy that my request for financial aid came through because without that, I would never have been able to start this course in the first place.

By Stephen M

Apr 9, 2018

Great review of the foundations of Data Science. I would have also included some background into the basics of database design, table construction, data file content examples from both relational/NoSQL (etc.) sources. Also, would be great to get a compare and contrast of the value of R versus, say, Python-Pandas and VBA because these are the other two free resources out there for handling data in some form (yes, I know VBA has limited applications in deep data science, but it IS still relevant in business analytics---a common launch point for the career of many would-be data scientists). All in all, superb work, folks. More please! Need input! (Johnny 5)

By Agustin A

Nov 12, 2018

Estoy bastante satisfecho con lo aprendido en este curso inicial del programa Data Science ya que es una buena introducción a todo lo que se verá más adelante. Debo decir como profesional de IT que me ha sorprendido cómo empieza desde cero explicando todo lo necesario para entender e instalar las herramientas informáticas necesarias para el curso con un nivel casi de principiante. Sin embargo en lo relacionado con métodos estadísticos y de análisis de datos el nivel no es tan bajo y los videos de la semana 3 han profundizado ya en algunos conceptos del análisis de datos. Espero que en los siguientes cursos se expliquen detalladamente desde cero.

By Nikolay B

Jun 17, 2019

Overall an interesting program is offered. Just started, an update is expected towards the end of the course. So far found an issue w/ quiz #1 (incorrect grading due a broken internal logic (?) where 2 different 'correct' answers are offered during subsequent quiz sessions). Also, I would say that the intro videos are too short to be useful. Anticipated scope is well aligned w/ modern trends that are re-branded from the underlying concepts known for a long time; such concepts were always being in the arsenal of any serious practicing engineer or scientist. Modern packages though are a nice compact up-to-date tools collection.

By Marco M

Sep 1, 2020

This is a very good course for beginners. The tools covered in the lessons and quizzes are indeed vital for contemporary data science. The suggested readings are very helpful and interesting, and the quizzes are also good. The only weak point of this course are the automated video lectures. They are quite boring due to the monotonic, computerized voice. Ok, automated lectures surely have some advantages, as explained by the instructors. But human emotions are key to learning. Thus, to promote accessibility for disabled students, there could be a mix of video lectures taught by human instructors and automated readings.

By Gurpreet S

Sep 5, 2016

I would recommend it to any one. The introductory course is so basic that some might see it not important but the course has done a well job by easily getting across the foundation of Data Science as well as helping non-programmers to easily drift into this field. I would have given 5 Star if i was allowed to attempt my tests even though i am auditing the course. The only thing coursera should benefit from is providing the certificate. By freedom of giving test and doing courses people will surely pay for one course or another when they get more confident with their results in audited course.

By Dan C

Oct 24, 2022

Extremely comprehensive. Well written and filled with interesting resource links for relevant content in nearby sites. While initially not expecting the Amazon Polly-based script reading, I came to like it; i.e., the fact I could first listen to each lecture adn then follow it with a review at my own pace of the same material visually.

I withheld the fifth star only because there were some broken links or content that could stand a review for updates, and possibly the tools have changed their behavior a bit, so that the steps provided probably need some tweaking. Otherwise; thank you!

By Brendan S

Jan 23, 2020

Solid starting class that highlights the fundamental software you will be working with for the Data Science Specialization. It holds your hand at the beginning, but familiarizing yourself with the software may lead to a few bumps in the road.

Some of the issues were due to unclear directions and, at one point, a needed additional package to knit PDFs from RStudio R Markdowns. While the forums are not very active, there are a few people who might be able to help you. Also, Google (along with the listed Data Science forums) is your friend when looking for answers.

By Paras B

Mar 9, 2018

The course was really constructive. However, for the students who are really new to coding, courses where creation of git hub account or coding to push/pull data from git hub is involved, i would suggest to add more videos related to step by step coding. Also, there are some irrelevant questions involved in the weekly quiz which are not very fruitful when it comes to learning this course. I would suggest these questions to be removed. Team can contact me on my email Id if they require complete feedback for such questions.

Hence I would rate this course 4/5.

By Marc F

Feb 29, 2016

I found this course a fairly easy introduction to the tools you will need for this series of courses, however I already had a rudimentary knowledge of Linux and Bash Shells. For the computer novice this may be more daunting. The one area that is worth spending some time on as an investment for the future is git and git-hub. Understanding how these work together is not transparent. It took me a while to figure out what I had to do to push committed files to a remote site. I think suggested reading could be more specific to guide people in this area.

By Marloes d M

May 18, 2020

The course was well structured and I compare him with two other beginner courses for data science. So far, the best one. I prefer following my own pace and opt for either video or script. The audio voice was a bit monotone but otherwise ok. I liked that there was some attention to data analysis background at University level but it was pretty basic. The final project was good since I had to redo it a couple of times before I submitted and those skills are now pretty permanent I guess:) Thanks for the clear (most of the times) guidelines.

By Ariel M

Feb 6, 2016

The Data Scientist’s Toolbox is a great way to dip into Data Science and the methodology behind it. The course is very general, and makes an effort to cover the bigger scope of things without delving deep in any. More than anything, it's a great way to learn the components and uses of data science and set a framework for all that will be coming after.

The materials are very well laid-out and almost feel like attending college classes. The visuals and slides are a little dry, but the pace is lively enough to maintain momentum at all times.

By Francisco J D d S F G

Aug 28, 2016

A light introduction to the Data Science field, in many ways it can be difficult for inexperienced people with software or inexperienced with stats - in my case it was not very difficult since some of the topics were already familiar.

The course can be done in a couple of days if the topics are already familiar, in my opinion the course's contents are perfect for someone very new to this field.

I would have rated more stars if the course's content was more "objective" for people unfamiliar with the subject - other than that it's perfect.

By Graham J

Jun 6, 2021

Overall a good course and got me to understand and do some things that I have never done related to data science. As a result, I would recommend it and will be continuing with the specialization. My recommendation would be to add more descriptions and explanations to make the material clearer. For example, sometimes it wasn't clear to me in which program to run a requested task, or what it means to fork. In order to to get through the assignments, I had to look certain things up on the web, whether websites or YouTube.

By Hathairat W

Dec 1, 2018

I got some bugs when running git bash and I had no clue how to fix them. I kept watching videos over and over but I couldn't find the answer. Then I tried google, reading many websites and doing trial and errors until the errors were gone. I understand in real life this is what I need to do but it would be good to know some proper ways of fixing errors after I submitted the assignment. So I can learn and use in future! Apart from that, the course is really useful and prepares me for the next stage.

By Erli L

Jun 3, 2017

It is a very good introductory course for anyone who would like to learn data science, or would like to use tools in data science for their everyday work (like me). In the course you will have some general essential ideas about what is data sciences and which tools are used in the science, and the most importantly, the concept of version control and the GitHub tool for the purpose. However, there will not be any in-depth knowledge in the course, which is determined by the introductory nature of it.

By Mehmet İ

Jan 8, 2022

Videos are interesting, but auto speaker is too fast to track, I think it should be slower between some sentences and paragraphs. Links should be added to the page which is talked in the videos. And it would be better with extra reading sources. I get to ask questions to students which they don't teach at class. It makes you think about what you've learnt and it is a learning progress I believe. But if they add extra-reading links and ask also from there, that would be better way of teaching.

By Carolina B

Aug 6, 2020

Es un muy buen curso teórico práctico sobre la introducción a la programación en R. Sin embargo algo que me desmotiva mucho es que las constancias no proporciones ningún crédito. Éste curso tiene una duración de 4 semanas y no me parece justo que no se tome en cuenta si se acreditó correctamente no tenga ningún valor. es el segundo curso que tomo en coursera y me pasa lo mismo, dos universidades renombradas que no proporcionan ningún crédito. ¿Cuál es el objetivo de ofertarlo entonces?

By MARIANA A O

Aug 19, 2020

This course is a pretty good introduction to data science, although I'm not sure how useful will these tools be in the future. Also many tutorials were unclear and I had a lot of problems to complete some lessons, I had to solve those problems by myself (difficult task sometimes considering I know nothing about data science). Anyway, I learnt a lot of stuff, in the end I recommend this course for an introduction, but check the content first to see if it suits your learning interests.

By Patricia P

Aug 31, 2018

On enrolling in this course I knew nothing of the data science world and always wondered how all that "jumble" of data was organized. After this short course I am beginning to have a glimmer of how this is done. I know there is more to learn and I am curious to know how. I must say that I struggled quit bit towards the end of the course with the assignment, but I believe as I continue with the other courses I would become more proficient using RStudio and GitHub, etc.

By Akshit M

Jul 7, 2016

Important note: Opt for this course only if you plan to do the entire specialisation. It is developed solely for the specialisation and not as a standalone course. You will not learn much concepts or theories or practice any R programming here.

In general this course was basic and good enough to get someone started for specialisation. The video lectures for setting up R, RStudio and Github account were helpful and very basic ( maybe coz I already had an github account).

By Howard G

Jul 28, 2020

A lot easier than I expected. In particular, compared with courses where one final project took longer than the rest put together, the project is just to put together your R/Rstudio/Github environment. There's a lot of value in that; plenty of courses you learn the concepts but don't add anything to your repertoire; if a year from now I'm putting a little project on my new Github site now and then, that will have more actual impact than a lot of harder ones.

By Nihad I

Feb 19, 2021

Course was very interesting, first 2 weeks were fantastic, but it will be better if they will give more information about Git Hub and its functions, because in some parts it is hard to get tasks done and some parts of Version Control lesson are not very clear. And i would say that using A.I and make courses is almost brilliant idea, but the voice is sometimes terrible and it gets hard to understand, also usually people getting bored because of monotonic voice

By Jonathan S

Aug 9, 2017

I wish this course would spend a little more time upfront saying at a very basic level what data science is and gave some real life examples of data science in action. Most of the course is configuring software that you will be using down the road, but it would help to know why you'd even want to use the programs and in general, what their capabilities are before you get into setting them up. I imagine that latter course will do this (at least I am hoping).