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

4.6
étoiles
26,578 évaluations
5,538 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.

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.

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4076 - 4100 sur 5,422 Avis pour Les outils du scientifique des données

par Swagatam M

Apr 01, 2017

Great course, you get to learn about the tools used in the Data Science specialisation.

par Joe K

Oct 07, 2019

Great! Nice foundation to help move forward in the Data Science by JHU specialization.

par Ryan L

Sep 16, 2019

Increase the default pacing. Recommending 4 weeks to install software is too generous.

par Pravinkumar C

Nov 21, 2018

Very basic course and that was how we should start learning the ocean of data science.

par Lee Y L R

May 24, 2018

Important course and introduction to the various tools for an aspiring data scientist.

par Joseph D

May 26, 2016

I ran into a few unexplained issues with final project but a very good course overall.

par Frank N

Mar 27, 2016

Very basic survey and mostly just setting up software, but confidence-boosting and fun

par Zee

Jun 27, 2020

A very good introducton to the tools, but the GitHub tutorials could use few updates.

par HanWang

Nov 27, 2019

The course is helpful, and material is well receivable. But not a fan to robot voice.

par Zhou Y

Mar 18, 2018

It is a wonderful introduction, and gives me a clear view of the track of the course.

par Jonathan A

Sep 19, 2016

Pretty good. Some lectures were good, a couple seemed rushed. Covered the basics OK.

par Alec k

Aug 22, 2016

Just an introduction course but helpful in setting up the rest of the specialization.

par Ming

May 06, 2016

Experimental Design is very great. Other contents are just fundamental for beginners.

par PUJITH R V

May 30, 2020

it gives you the basic understanding or lays down a foundation for the later courses

par Jaya S

Apr 21, 2020

Know i am done with toolbox and looking forward to complete full data science course

par Gabriel E B

Apr 14, 2020

It's the basic introduction to all the tools you will use for the Data Science Spec.

par Tejas B

Sep 30, 2019

Great Into course! It's always good to get the basics right before the greasy stuff!

par Jack C

Jun 30, 2019

Great course - a few grammatical/syntax issues in the quizzes but otherwise love it!

par Daniel M D V

May 18, 2019

Very basic course to set-up the necessary tools for the specialization. Nothing more

par David R

Jul 31, 2018

A good overview of the tools needed for the rest of the data science specialisation.

par Amol G

Jul 16, 2017

Elaborate and precise course for beginner introduction to the wide range of courses.

par Axelle R

Apr 03, 2016

Good introduction to tools if you don't know them already. Otherwise very remedial.

par Dominique G

Feb 06, 2016

Good introduction to data science, primary tools and what the spec. course is about.

par Mwenge M

Jun 15, 2020

machine read lectures are not as easy to follow as those presented by human beings.

par ABHINAV P

Jul 13, 2018

Gives the initial set up knowledge and idea into the field in a very structured way