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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

4.5
21,702件の評価
4,344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
Introductory course
(1056件のレビュー)
Foundational tools
(243件のレビュー)

人気のレビュー

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.

AI

Apr 24, 2018

This course was a good intro especially in setting all the necessary software for future courses. I suggest to read the manuals, books and other readings the profs suggest. The resources are helpful.

フィルター:

The Data Scientist’s Toolbox: 4026 - 4050 / 4,217 レビュー

by Florence C

Nov 08, 2018

I wonder if most of students who took this course would have expected to keep installing software, one after one, and seems never end. For the whole week course, there is nothing related to the course. The worst part is that once I got into trouble to get a software work, I got stuck. I spent hours and hours to search for a solution on the web. However, most of the answers are too technical for me to understand. Although I understand that data scientists have to use some computer programs to assist them to the work done, I don't think that, as a novice, at this stage I need anything like GitHub or git to help me learn the subject. Moreover, I'm not sure if I would be taking another data science course yet.

by Cándido O M

Oct 02, 2017

Too basic material. I had to watch everything x2 faster to keep my attention. This course is just an overview of the topics that will be explained in the next courses, which could be much shorter in just one lesson or just avoid it. It is only useful to have R and RStudio installed and to introduce you to GitHub if you do not already know it.

I think it would be an improvement if you made the videos longer in order not to repeat yourself. Because sometimes you are constantly reintroducing a topic and never getting to explain much of it.

I hope that the rest of the courses be more direct and easier to keep my attention on, because I really what to learn about this subject!

Thank you

by Julia S

Mar 01, 2017

This is really bad structured. As analogy - imagine a cookbook that says: in chapter 8 you'll learn how to cook pies, but here in introduction let me tell you how to add baking powder in them. It is not useless information it is just very out of place.

Learning some git commands was the most usefull in the course for me. (Though again, why would you first show the commands and just after that explain what's the tool for and where to download it?)

And by the way it takes half a day to cover all 4 weeks material (listened through all videos, installed the tools). Which is not bad, just of other users information)

by Lenka " P

Apr 19, 2016

It is a nice introduction, but the material is barely worth a one week orientation lesson (I have completed it in about 4 hours with watching all the videos, taking detailed notes, and completing the quizzes for 100%) . Why should we pay for a specialization preview, we can read info about the separate courses on our own? I am really looking forward the next courses in the specialization since I really need a good course in statistics and this seems to be one, but the first course should be eliminated. The installation of R and github account videos should be added to the next course as an introduction.

by Claude R

Mar 05, 2017

A very big difficulty for me, French people who uses to speak english everyday for may work is that :

1) Teachers don't do any effort to speak slower and to articulate

2) As with all other courses I've attended in english, it's impossible to read a transcription, even in english, while reading slides.

Slides are not sufficient by themselves, i.e. without commentary beside. The workaround I've used is to print french translation or english transcription and read it, trying to guess which part suited with which slide ...

For a non-free course, it's not really professional ...

by Amy-Louise S

Sep 24, 2018

The lectures were very uninspiring for the most part and I felt that my practical understanding was poor. The forums were also not particularly helpful as I saw Moderators mocking students for asking valid questions based on their inexperience with Data Science. I spent most of my time finding better tutorials on YouTube, so really.... I have a certificate but don't owe much of that to the course in question. It only becomes worse as the complexity increases with the rest of the Courses in this Specialization.

by Sem O

May 11, 2016

The course is well structured and provides a good introduction, however, I expected a bit more from a course that costs 20 pounds than just a few clips on how to install and set-up software/create a github account etc. This information is available for free online on the websites of the respective software.

I understand that such an introduction is needed for the course, but then do not offer it as a separate 20 pound module. Instead include it for free with any other 'specialization' you can buy.

by Tarik G

Apr 28, 2018

I can see that the lecturer's intention was giving an overview by mentioning all different topics, however, it just got me confused. I wish it was more into a solo topic. It would be great if it was given only git/github lectures, so we, the students, can be more comfortable when it comes to uploading files in the following courses. I see in the discussion forums that github is a problem for most of the students in the forums.

by Sydney R

Feb 05, 2016

You will learn some command line commands, git, Github, and what you will need for eventually using R.

I was a bit annoyed that this course is a requirement for the Data Science certification (which is what I am after). I already knew everything taught in this course and was a bit annoyed I had to pay for this in order to complete the track. I think 'courses' that are fully setup like this should be opt-in not required.

by Ignacio S U

May 23, 2017

The course is extremely introductory and even though it may lead you to references you may use to self-teach yourself, it is not worth taking a four weeks course for a one week content. At the end of the week you will have about three new programs installed in your computer and no idea on how to use them for practical situations. Although it's intended as introductory, it surpasses that barrier to mere spectacle.

by Daniel P

Sep 09, 2019

In my opinion, the content of this course is too basic and little bit of topic for the data scientist specialization. Of course it is useful to be able to use git, shell etc. but I believe that most of the people already know those and the rest of the students can be redirected to relevant study material. All in all, there was about 90 minutes of relevant study in this course.

by Ben V

Sep 13, 2016

Very very introductory. I didn't find the tooling aspects of this course particularly helpful, but I'm not in the target audience. It's length was misleading -- I completed the work in two days easily, but I am a technologist, and already had the tools installed. If you use GitHub and RStudio, the meat of the course is only about an hour of the lecture.

by Daniel J R

Jun 20, 2018

Not very engaging videos. Superficial introduction to the mechanics of some tools without providing much context. Final submission did not work per video explanation. Need a more engaging presenter. Not quite at the level of Prof. Ng's Machine Learning course which I realy enjoyed and learned a lot from.

by Heather G

Mar 21, 2016

This should not be its own course, as it would be pretty useless if you were doing it on its own without doing any of the other courses. The end of course project literally being just to make a Github account and download R-studio could be quickly covered in the first week of the other courses.

by Raj K P

Nov 14, 2017

showing - doing things live in the video would have been great .. it seemed like explaining a PPT by an instructor. You could have taken one data set and have done all shorts of things and then in the midst thrown some quizzes to student instead of going though all the discussion in one go

by Lyn S

Aug 10, 2017

Not bad, but certainly not good. I cannot believe there is a style of teaching where you never get to see the best way to do something. I can slog thru the programming, but I doubt it's the best way to do something, but I never get to see how something should have been done.

by Eric J S

Aug 06, 2019

Very basic course. Poorly motivated, material presented without an effort to demonstrate why. This is not entirely out of place in this intro course, but it permeates the entire program. Difficulty poorly controlled, projects and quizzes much more advanced than lectures.

by George C

Jan 13, 2018

I personally think that this course should be better interwoven into the other modules of the data science specialization. It's a quick primer, but aside from that, not very valuable in terms of the information that it's providing. I wouldn't pay $49 to take this course.

by Thiên P T N

Jan 30, 2016

It is generally good course, but I feel it is just a combination of very little tools, skills and ideas. I believe it is quite complicate for me to understand, esspecial git and github. I think it is better to combine this course in other courses where you need it.

by valentine

Aug 27, 2016

Would like to have seen more material using git and git bash commands. More repetition here would be helpful. Seems like a lot of this information will be lost or forgotten when it comes time to use it, especially as it relates to the Data Science Specialization.

by Roy H

Jan 17, 2016

Dry videos. Most classes are someone showing how they do something their way, rather than guiding or teaching with the intent to have the student absorb and re-apply principles.

Very difficult for a student to absorb material from this video series

by Derek P

Jan 06, 2016

Hard to follow with a lot of technical intructions right off the bat with inadequate explanation, a lot of "read more about this at <insert URL>." Videos were boring and the instructor was invisible just reading off the slides. Not very engaging.

by Tarunoday S

May 06, 2017

This module should not be kept as a separate piece...The steps mentioned in the lectures does not properly cover what is asked in the assignments.The lecture content needs to improve to cover the assignment

by Marie J

Feb 26, 2019

I found this informative but you do not get much in terms of service. One of the quiz has a technical issue and I made a complaint weeks ago, but I still haven't gotten a response. Nor has it been fixed.

by Alessandro V

Oct 22, 2016

It is too easy as a "university" course. It is much more like a pratictioner course. The final exam is ridiculous, really too easy.

It can be thought as a week course instead of a four week course.