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Avis et commentaires pour l'étudiant pour Les outils du scientifique des données par Université Johns-Hopkins

4.5
21,144 notes
4,217 avis

À propos du cours

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....
Points forts
Foundational tools
(243 avis)
Introductory course
(1056 avis)

Meilleurs avis

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.

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1 - 25 sur 4,088 Examens pour Les outils du scientifique des données

par Jitin V

Aug 13, 2018

Good to set you up for advance courses.

par Tolga T

Nov 24, 2018

!!!STOP DON'T TAKE THIS COURSE!!!

%100 pure advertising. There is a moment I felt like I learned some thing, but rest of the course I played with x2.0, of there was more I would have get it.

Putting this into Specialization requirements is smart from your perspective, you are basically saying if you want to reach Capstone pay me $50 more, but at least fix the typos you made during video, just a little respect to your subscribers. But right now, I highly doubt that Capstone Project will be something serious that I want to mention in my Linkedn. There is also downside of what you do. But since you are in between the top rated courses either nobody uses Coursera anymore or people are silent enough and patient enough.

You are all Scientists like me, I'm also biostatistician but I would never ever post a course like this to any platform. I'd rather use Google or Facebook ads to lead people here.

If somebody wise enough to get Data Science Course, he should be skillful enough to download R, click next and install it, and R has help for it, shows you step by step. GitHub is free platform, anyone who can signup for Coursera can signup for GitHub, too.

I know there is no requirements for this course or specialization course, it is 0 to Scientist but seriously you are talking about R codes, arrays, loops, regression, model fit but signing up for GitHub.

Your target group in Coursera is either Data Scientist or becoming one, so they know what the Data Scientist job posts requires.

It requires coding blind folded R/Python/Java/one of C family at least 2 of them, hopefully all of them.

It requires SQL, MySQL, NoSQL, any kind of SQL or database solution mankind ever used.

It requires Math, Statistics, Analytics, Algebra, Finance, Economics + all kinds of computational sciences

It requires management, social relations, advertising, psychology, anthropology + rest of the social sciences.

+++++ it requires LOGIC and NON-ARTIFICIAL HUMAN INTELLIGENCE

so we are trying to be that guy, no need to show installing R or GitHub, I'm sure you will do it again doing rest of the Specialization.

par kaan b

May 28, 2019

Not met what offered. I really don't know why but Instructor was in a hurry and like, he was in the position of instructor by obligation.

Maybe, He has knowledge of the subject, but definitely does not have even basic skills of teaching.

Because of this course, I am not planning to follow other courses on this specialization.

par Annette I

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.

par Anthony V

Aug 16, 2018

Great course, really helps get you into the right mindset for becoming a data scientist.

par Frederik C

Aug 13, 2018

Great intro

par William C

Sep 26, 2017

I really don't know much about this stuff, I think the jury's still out on whether the last four weeks will be helpful in the future. We'll see how much I think I've learned at the end of the course

par SANJEEVE K G

Jan 24, 2019

Coursera has given new life to me

par anubhavbbd

Aug 01, 2019

it was simply the best

par Luis R

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.

par Alexander M

Jul 22, 2017

Great Primer for what Data Science is about. It also provides the infrastructure of tools needed. This was what I was after, a way to provide other data scientist hardware and infrastructure support.

par David S

Dec 20, 2018

This course was in many ways the first day of lectures, get your syllabus, buy your books, install your tools, etc. I would give it 5 stars but the lectures inclusion of internet addresses that aren't links and aren't included in the transcript led to a lot of time paused and typing out long addresses.

par Andrea R C

Apr 11, 2019

A great intro to the course. I am not the biggest fan of the automated voice, but it gets the job done. I do like the secondary lessons written out with bulleted lists and close-ups of the slides. That is like a helpful review.

par sonal g

Feb 03, 2019

Providing feedback means giving students an explanation of what they are doing correctly AND incorrectly. However, the focus of the feedback should be based essentially on what the students is doing right. It is most productive to a student’s learning when they are provided with an explanation and example as to what is accurate and inaccurate about their work.

Use the concept of a “feedback sandwich” to guide your feedback: Compliment, Correct, Compliment.

par Khaleel u r

May 22, 2019

execellent i am very to gland get this certificate .. it is so valueable for me. the first one of data science track

par JEFFERSON D S N

Aug 31, 2018

SIMPLESMENTE SENSACIONAL !

par Aryan G

Jul 01, 2019

This is a very good course as it tells you some basic and is mostly the introductive course for the entire specialization.

par Darky C

Nov 28, 2018

Pretty good in explaining the basics of data science

par Adeyemi O A

Jan 10, 2019

Very good course for beginner in data science

par Usenaliev N

Dec 08, 2018

Would be great to have more reading materials

par Aman U

Jan 05, 2019

Good but need more explanations for topics.

par PALAKOLLU S M

Aug 10, 2018

Teaching of lessons are simply amazing.

par Jasmine P G

Aug 16, 2018

The course is clear and good to learn,

par SOMA C

Jul 31, 2019

More clarity on creation of .md file should be included in lectures

par Pratyush M

Aug 13, 2018

A bit basic, but a great start for beginners.