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The Data Scientist’s Toolbox に戻る

ジョンズ・ホプキンズ大学(Johns Hopkins University) による The Data Scientist’s Toolbox の受講者のレビューおよびフィードバック

4.6
27,577件の評価
5,801件のレビュー

コースについて

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....
ハイライト
Foundational tools
(243件のレビュー)
Introductory course
(1056件のレビュー)

人気のレビュー

SF

Apr 15, 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.

LR

Sep 08, 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.

フィルター:

The Data Scientist’s Toolbox: 5076 - 5100 / 5,667 レビュー

by Pedro V Q d C

Sep 27, 2016

I think the course was too superficial and didn't cover enough topics to be a standalone course. It could be part of a greater course. My feeling is that this wasn't worth $30 dollars, and that such a small course was put together just to charge for one more module.

by Ryan W

Aug 21, 2018

As an intro, this course is probably pretty good. I, however, already had experience with R (although the refresher was useful). However, if you've taking a data science or machine learning course recently, I'd give this one a pass and head on to the next course.

by Shady E

Nov 12, 2016

Thank you for the fantastic effort. Here's some constructive feedback on the course.

It's a very basic course, could have included more material. Also, the audio quality is not that great. To make it better, I'd Include more walkthroughs for Git and GitHub.

by Diego L

Mar 08, 2017

Too little substance, though I do expect the rest of the series to be good as I take this as a setup course and my expectations for those are high. Having said that, perhaps it would be wise to charge less for this initial course or even offer it for free.

by Alejandro M

May 11, 2020

Some parts are good, but the presentations are something very boring because the fact that are 'automated'. Is the first course and the concepts are very basic and sometimes well explained but i expected a more interactive course. 3.5 / 5, maybe 8 / 10.

by James

Dec 01, 2016

Really tough to review this class outside of the context of the other elements of the data scientist specialization. What was presented was straight-forward and quite well done. After I know how well prepared we are for next classes, I will re-evaluate.

by Ced W

Apr 20, 2016

This is a course to get you set up with all of the tools that you will need to go forward. No hard homework, but you will be ready to work. The intros into various aspects of the curriculum also serve to prepare you mentally for the coming weeks.

by Vasilis S

Feb 18, 2016

Useful steps for starting the specialisation, but should this really be a course that people are paying for? Come on guys. By the way, some R programming concepts could be introduced here and de-clutter the congested/crammed R programming course.

by Sunny S

Apr 04, 2017

This course is a good start to give an overview on the toolbox you should be aware of to specialize in Data science or analysis. You don't need 4 weeks to complete to complete it! At best you could complete within a week or 2 days. Best of luck!

by Nicolas B P

Oct 04, 2018

Not sure if we will come back to Git, but i thought that in this section it was covered way too superficially. Maybe the idea was that we should get to it ourselves, but i guess my expectation was different. Other than that, the course was ok.

by Oscar C M

Jan 17, 2017

Some video explanations are not so clear, so will be great to highlight some concepts, theory and methods or technical (with some reading), also will be great exhibit the latest news about toolbox(that is the current topic) or data scientists

by Rosina P

Aug 12, 2017

This course stays on the surface and doesn't delve too deep, probably in order to not scare off people who are new to the subject. From what I've seen in the second course, the material becomes a lot more difficult, which I was glad to see.

by Francois B

May 29, 2016

Would have like to jump straight to the material. Although I understand some may need it, the command line course was pretty basic. This course on it's own doesn't give much. One can get started with Programming with R w/o missing too much.

by Richard B

May 26, 2017

Fairly basic course covering the fundamentals, I would suggest to most people to complete this course concurrently with the R programming course or to complete it all in one go, as I personally completed it within a couple of hours or so.

by Tejaswini C

Oct 31, 2017

While this is a good introduction to Data Science and the tools available, it might feel a little too elementary if you have had prior exposure to the subject. The final peer review project could have been a little bit more challenging.

by William L A E G

Mar 29, 2020

It did not meet my expectations. It is more an informative course than a specialization course. They thought they were going to go deeper into the use of statistical programs, they only cover details that you can discover for yourself.

by Robert A

Feb 18, 2016

I have mixed feelings. It was WAY too easy for me, but my wife did it too and it was about right in difficulty for her. But either way, I felt like it just taught you to install stuff rather than actually teaching meaningful material.

by Shirli N

May 29, 2020

A good course as an introductory course. My career aspirations are not to become a data scientist so I don't know how much I am going to use the Github. Time will tell. I really enjoyed the videos and how the course is given. Cheers

by Doug H

Feb 11, 2016

Too easy if you already know anything about github or Rstudio, although I do understand the need for an introductory course. The "Experimental Design" video was the only really useful part and contained quite entertaining examples.

by Joseph Z

Feb 22, 2016

This is a very basic course. If you are already a software engineer you could zoom through this entire course in an evening. If you are not a software engineer and don't know what things like github are, this class could be useful.

by Shrief M A E

Apr 22, 2020

it is not the best way to start your data science career for me as a student because it has a lot of reading and theoretical ways I don't think its good for a beginning start and I was hopeful for more practice I would love to do

by Randy c

Jun 05, 2018

Beginning course in Data Science spent too much time on tools and not enough time on concepts, possible solutions and application. Seems like I spent a lot of time in the weeds of application installation and repositories. humm

by Luis E B P

Feb 07, 2018

I believe that in some of the assingments the student is asked to do a few things that werent taught in the course. And also during one of the quizzes the platform wasn't working propperly, and I had to answere it many times.

by Yufei W

Jun 27, 2018

I don't find the contents about R, git, and GitHub very helpful. They are way too brief and perhaps work better in those specific courses where we have a change to use them. Solely learning some commands is not very effective.

by RAYMUNDO R M

Jul 04, 2020

A pesar de que el curso lo menciona, es demasiado introductorio, no profundiza nada y en mi opinión se pierde mucho tiempo viendo lo de GitHub. Aprendí muy poco de data science, lo demás lo sabía de los cursos de estadística