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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
28,835件の評価
6,114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: 4076 - 4100 / 5,977 レビュー

by Rahul P

Jan 25, 2017

Very nice introduction! Unlike a lot of online courses, this course is no fluff or jargon. It is solid stuff with hands on experience. I only wished this course was longer. After completing the 10-week Machine Learning course by Andrew Ng, this course felt a bit too short. :-)

by Colin L

Mar 31, 2020

Very basic. A few tweaks are needed in the last quiz's questions - the one pertaining creation of a .md vs. a .rmd file, and how to make sure the "## " prefix is properly given. (There should be a space after, and graders need to look at the raw file, not the presented view.)

by Madhusudhan T

Mar 24, 2018

An interesting introduction to data science, Git and GitHub. Hope GitHub is explained in a little more detail. Quite a few people found a couple of problems with the final project. The community is great and there are people who will help. Looking forward to the next course!

by Tina L L

Apr 28, 2017

The course is great but there are some serious glitches happening in the Coursera platform that desperately need attention. I just went from showing that I did not pass the peer review section and in the next second was greeted by a big green Course Completion Certificate.

by anjali v

Apr 01, 2018

This course is a great introduction to what data science essentially is and all the necessary tools required to start your analysis. However, it would be great if the examples used in the videos were explained a bit more in context rather than being stated plainly.

Thanks!

by Zainul A

Dec 21, 2017

A little unclear about the process for using Git & Github. The common functions/code are thought, but I believe a demo or a video review for the last assignment should be shared. Other things in the course provide a good introductory insights to the world of Data Science.

by Tanmay B

Mar 23, 2017

It is a really nice course if you plan to complete all the 10 courses in the Data Science Specialization track. As a standalone, It is not that great a course as it basically introduces you to different things and you need to do other courses to actually learn something.

by William B B

Mar 07, 2019

This is an excellent basic course. The main problem I had was understanding the computer voice at times. There is also a quiz question or two that refer to commands in Studio that are not up to date, but only a couple that I found. All in all, it's an excellent course.

by Naveen K

Nov 27, 2016

Great intro to Data Science Specialization. Hoping to complete the other courses as well. Dispels my myth about Data Science is all geeky stuff. Looking forward to bust more myths.

This course is light, broad and introductory. 4 weeks is a sweet spot. Keeps you engaged.

by Apolline M

Oct 23, 2016

Not much to learn, I would have liked a more thorough introduction to data science's principles.

Yet, everything is really presented step by step to make sure that all participants install correctly all tools needed for the further classes included in the specialization.

by Tony D C

Apr 06, 2020

This course is perfect to get an introduction to R and RStudio and the Github. It's easy to follow and pretty fast to complete. Probably the best thing you take home from this is to have a nice setup for the following courses where you can use the tools presented here.

by Bernardo M F d S

Mar 09, 2018

Although I understand that Data Science involves a lot of self-oriented research, more resources and recommendations for learning git basics would be appreciated. Perhaps some practical exercises before the final assignment would've ensured a better learning process.

by Rok B

Apr 04, 2019

It is a good start to data science, you don't need a background in programming. The course is aimed at 1) helping you set up R, RStudio,git and conect it to GitHub and understand it's basic functionality and 2) getting a basic understanding of what data science is.

by REDROUTHU B

Jun 18, 2020

The track consists of 9 courses that each last about 4 weeks which are released in batches of 3 courses each month. This course introduces the very basics of R and R studio, Git and Github and a few otherthings that will be used in the data science specialization.

by Brandon T

Nov 17, 2017

A little daunting at first but the instruction is simple and the ability to search video transcripts for tidbits basically saves me the step of taking notes. Some of the navigation was difficult in the forum, but I ended up figuring it out and posting something.

by Benjamin S

Sep 06, 2017

Good starter content, data science background and overview of tools. Could provide more lecture time on the tools (RStudio, Git/Bash). The course is labeled for beginners, but I can see where someone without much experience could really get intimidated by

by Vinayak

Aug 01, 2019

Well structured and nicely organized. Content is great and lays the ground rules for start of statistics using R.

Minus one start only because there's no instructor teaching the course. I would've preferred a real human voice rather than an automated voice.

by Vishnu K

Jun 26, 2016

The videos might not seem a lot at first view, but they contain links to some of the most useful material out there. The mentors on discussion boards are immensely helpful as well. For the uninitiated in data sciences, this is a great module to begin with.

by Steve S

May 08, 2016

Good pace for the first course. A little more guidance on Git command flow would be help. However, the available Help documentation on Github did the trick. The problem was having to work primarily in the command line which provides limited feedback.

by Francesco B

Jun 10, 2019

Well done, but very basic. Only do it if you are really completely new to the subject.

The audio part is entirely done using automatic text reading. Very well done compared to other similar tools, but still the experience is not the same as with a human

by Natalia S

Sep 07, 2017

Videos are already sort of "old". Having Macbook i had significant problems with pushing files to GitHub repo, nevertheless I was doing everything said in the videos.

I could do that after using some other functions that were not mentioned in the video.

by Leonardo A

Apr 22, 2019

It was straight forward. However, there were some difficulties installing RStudio using the latest version. I had to go the previous one .e.g. Latest was 3.5 I used 3.4 matching RTools. Other than that very straight fwd, including Github (basic) usage

by Scott D

May 07, 2020

A good course with clear instruction that gives you a basic review of using data and installing R and related programs. Occasionally necessary steps in R are omitted and one has to do some googling. Not a fatal flaw, but frustrating for a beginner.

by Roberto R

Jul 23, 2020

It felt a bit like a RPG tutorial where your big accomplishment is learning how to run or crouch, but I guess it makes sense for it to be part of the Specialization track. I would recommend it as part of a series, more than as a standalone course.

by Carolyn A

Feb 08, 2016

Great introduction to the different tools that a data scientist will encounter and use, including RStudio, Git, and GitHub. I would have appreciated more practical experience linking Git and GitHub, as that is critical for version control of code.