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Вернуться к Набор инструментальных средств для специалистов по обработке данных

Отзывы учащихся о курсе Набор инструментальных средств для специалистов по обработке данных от партнера Университет Джонса Хопкинса

4.6
звезд
Оценки: 27,604
Рецензии: 5,807

О курсе

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....
Основные моменты
Foundational tools
(рецензий: 243)
Introductory course
(рецензий: 1056)

Лучшие рецензии

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.

Фильтр по:

5351–5375 из 5,686 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: BILASH P

Jun 04, 2020

This course is good. But automated video is so annoying.

автор: Jacob P

Jul 01, 2019

Seems to be somewhat useless in terms of actual content

автор: Anandwade N

Feb 25, 2018

give you good basic for data science and tools required

автор: Joshua K

Jul 05, 2017

Pretty Basic, but helps get you in the swing of things.

автор: PRABHAT K

Jun 09, 2017

Good for understanding tool and how to work with Github

автор: Avi C

Jul 20, 2016

Just an intro and learning a bit about Git and Git hub.

автор: Victoria M

Mar 14, 2016

Doesn't provide a strong enough base for R Programming.

автор: Anagha J

Feb 07, 2016

Good and basic understanding of terms.

Can be made vast.

автор: Jay P D

Apr 08, 2020

Just the basic setup... pretty slow but informational.

автор: Morgan A G

Feb 18, 2018

Very easy, I am unsure if this is a good thing or not.

автор: Rafael C

Feb 16, 2017

Good course, but worth only for really basic learners.

автор: Vivek K

Jan 08, 2017

Not really a course, should just be Week 1 in course 2

автор: Veli-Pekka V

Oct 22, 2016

Covered basic elements of data science and statistics.

автор: Mauro P

Feb 07, 2018

I would like to see more practical exercises about R

автор: Zin

Sep 26, 2019

It was helpful in getting to know R and R packages.

автор: Smit A K

Mar 26, 2019

The entire course can be explained in 2-3 lectures.

автор: Alaa E D H

Jan 14, 2018

this part is not necessary, keep it optional please

автор: Juliana C

Sep 25, 2017

Very introductory course, give an overview of tools

автор: Renata G

Jul 03, 2018

Good course, but lectures are sort of superficial.

автор: Rob L

Mar 22, 2018

Maybe a good basic intro course, but quite simple.

автор: Suhas K

Apr 24, 2019

I wish there were more exercises for the project.

автор: Vasilis Z

Jan 16, 2017

nothing special, no significant knowledge gained.

автор: James P

May 28, 2016

Later courses are better. This one is quite easy.

автор: patrice j

Feb 23, 2016

Good but needs more assistance with the students.

автор: Xiaojun L

Mar 31, 2017

The git and GitHub section is not very clear....