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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
30,005件の評価
6,396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....
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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

LR
2017年9月7日

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
2020年4月14日

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.

フィルター:

The Data Scientist’s Toolbox: 4151 - 4175 / 6,255 レビュー

by Rajath K

2020年5月12日

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by Ловягина Ю А

2019年3月18日

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by Parth M

2019年2月25日

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by Jonathan A F

2019年1月6日

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by Veene V

2018年9月13日

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by Fabio H R S

2018年8月23日

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by Marco G

2018年3月5日

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by Baranikumar T

2018年2月20日

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by Beatrice S

2017年12月19日

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by Seok Y K

2017年8月10日

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by ROTIMI, O R

2017年8月8日

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by Govind R A

2017年8月7日

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by Kyle D

2017年6月22日

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by Rogelio N

2017年5月9日

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by Sujana M

2017年4月14日

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by Park, M

2017年1月16日

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by Andy N

2016年8月15日

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by jim h

2016年3月4日

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by Shweta_Jha

2016年2月8日

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by Enrique B

2015年12月4日

I'm doing this training for the second time, now as a beta-tester. Particular comments about lecture content, problems, etc. have been put in every lecture.

General comments, in short:

1) Related to the new platform and UI design:

_ It is cleaner and simpler than the previous one. I like it, BUT...

_ It lacks of some useful features: saving intermediate results in quizzes before submit them; calendar; limited number of subforums.

_ The most relevant flaw: there are not downloadable versions of lecture slides. Unacceptable! No way to check most of the links we saw in slides (URLs not visible).

_ Description and steps in course project appear "too packed" together. I prefer the former design.

2) Related to content:

_ The course is mainly for preparing students for the rest of data science specialization program. When you said "toolbox" you mean the concrete toolbox you will need to do the program. Some people expect to have a general introduction to data science but that is only a half of the content. I think this is clear enough in the presentation but for some reasons there are people in forums who protest the content, so maybe you should insist more in this fact.

_ I would like to suggest some kind of reorder of material: week 2 is all about installing a running tools and week 3 about key aspects of data analysis. Maybe you can split both types of content between wk2 and wk3 to make wk2 more appealing for not technical oriented students.

_ Git is a source of problems for a good portion of people. See my comments in lectures about how Git is explained.

by Krish H

2020年4月27日

So why not 5 *'s - because I could not give 4.93 *'s

What I found excellent and thus 5 *'s - *****

a) material

b) even the automaton of a voice - was not a deterrent but rather soothing - oh well tells you something about me!!!

c) Material is deceptively easy in the front end and gets progressively more difficult later

d) the references are well thought out even of the entry into Data science

e) The build up is very logical

f) Lots of thought has been put into the design by the team

What I found lacking and thus dinged a couple of points (perhaps too harshly)

1) The mini quizzes do not sufficiently force you to think about the material and thus easy to breeze thru to the next week - perhaps I am being too judgmental and it may improve in the next course of the specialization

2) I could not see an easy way to get the material to review when taking the test - most of the time I forced myself to not look at the material to test myself but the onus is on you

3) It should not be about getting some questions wrong but learn the material so that every question can be right (imparting knowledge vs getting a certificate with 80% pass - think how would we feel if this was a training for a neurosurgeon ;) ) - a suggestion would be to force the student to read the section that pertains to the incorrect answer and not allow the test to be taken again until that is accomplished - like in a class room setting.

by Isabelle A M B F

2020年7月21日

This course is a great intro to the potentials of R and the world of Data Science and Big Data as well as the approaches and mindset needed for it. It's fairly straightforward, my only suggestion is to maybe include some tips on troubleshooting some installations for some parts of the lectures. For example, I already had R and Rstudio installed from my college days, but the versions were outdated (R 3.2.3) and weren't compatible with some packages and they weren't working but I wasn't understanding why until I had to google it. Similarly, I had some issues with linking my GitHub account to my Rstudio because the route it was using wasn't working and the correct one was highly similar, I was only able to fix it thanks to forums. These details can be frustrating for someone who's trying to follow along with the lecture but is stuck, so thank god for forums. It would be nice if the instructor could write a couple of tips on how to fix some common issues like those for novices.

by Jacob N I

2020年10月25日

I understand the decision to use synthetic voice, but at some point it gets boring and uninteresting because of the lack of variety in the tone and loudness. I still get reminded from time to time that the voice I'm hearing is AI generated. But besides this, the course content is a good way of introducing a beginner in the environments of GitHub, R, and RStudio, although personally I still don't fully master how I to connect these different platforms or languages or interfaces. Particularly, the lesson on commit, push, and pull and how to these tasks are supposed to be done in and across the different platforms (including GitHub) still confuse me. The programming per se does not worry me as much as getting the file paths and directories right and making sure that I am where I am supposed to be whenever I do a task. Lastly, I believe there are some typos in the transcript so please review and make the necessary corrections.

by Jeremy J H

2016年8月1日

Excellent Course for learning Basics. I had no previous experience with software, computers aside from surfing web, checking e-mails and some Microsoft Office. I'd recommend this course to anyone Interested in data-science or coding in general. The course is easy but not too easy the frustration of dealing with computers exists and I feel it was important for myself to struggle a little bit. I followed the advice of the instructors and sought out solutions to issues. I spent twenty hours a week but if you are tech savvy, take good notes, follow directions and everything goes as planned you could possibly get through the course in a lot less time. There are also a lot of people willing to help. The course shows you how to seek out help efficiently. I didn't request any help this time around had I done so I would have spent half as much time on the course.

by Kit T

2017年6月11日

I think this is an excellent course. If I could I would give four and a half stars. The only reason I wouldn't give it 5 stars is because I would prefer to have my work graded by an expert rather than my coursemates. I tried to mark as fairly as possible but didn't know whether I'd done one of the questions properly. So I marked other people down on where I thought I'd made an error (but wasn't sure whether I had or not). I think this could be potentially unfair to people as they may have got it right. If an expert had marked all the work then we would all be sure that the assessments were correct. This is quite a big deal when it comes to confidence in one's own progress moving forward. However, I thought the content was great and easily accessible and I am looking forward to continuing the course.