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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: 29,942
Рецензии: 6,387

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
7 сент. 2017 г.

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
14 апр. 2020 г.

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:

4901–4925 из 6,246 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: M.Reza

26 авг. 2018 г.

it could be better if the local repository in git was explained more.

автор: Sam M

3 апр. 2018 г.

This was a good introduction. I would have liked to see more content!

автор: Javier K

31 янв. 2018 г.

Está muy bien para iniciarse y tener en cuenta los elementos básicos.

автор: Kirstin L

10 авг. 2017 г.

Could have used a little more details in explanations. Overall okay.

автор: Jason L

26 июля 2017 г.

Git and Github lesson could use some better explanations and examples

автор: 廖倩华

15 июня 2017 г.

Basic information on data science and the toolbox of data scientists.

автор: Damien B

6 июня 2017 г.

Very logical in stepping the knowledge but some times short in explan

автор: William K

5 июня 2016 г.

Very helpful introduction to downloading R and Data Science concepts.

автор: Davide A

25 авг. 2020 г.

Nice introductive lessons on how to deal with R, GitHub and RStudio!

автор: UMANG A

24 мая 2020 г.

I prefer non-automated video lectures over these automated lectures.

автор: Paul F G

6 янв. 2019 г.

Very good, concise overview of the burgeoning field of Data Science.

автор: Bernardo L

6 авг. 2018 г.

Quick & simple (yet useful) introduction to data science principles.

автор: catherine s

25 июня 2017 г.

I enjoyed the course and the learned some useful skills. Thank you.

автор: Sachin G

24 мая 2017 г.

learn what basics you need to start as a data scientist. Really help

автор: Reinier F

24 мар. 2017 г.

Excellent introduction... Cant wait to get going on the next course.

автор: Tena

9 мар. 2017 г.

Great course, but maybe there should be a better explanation of git.

автор: Deleted A

26 сент. 2016 г.

It is a good introduction to the Data Scientist Tools and processes.

автор: Richard T

17 февр. 2016 г.

Clear and concise. Can be completed in a very short period of time.

автор: Jeffrey L

1 февр. 2016 г.

Just shows you how to install rstudio and github, rather slow-paced.

автор: Scipione S

25 сент. 2020 г.

I did not appreciate the robotic voice, it is a little bit annoying

автор: Robert M

16 мая 2020 г.

So far this has been a very well laid out course. extremely pleased

автор: Karla P V d O

28 апр. 2020 г.

I understood the reason why is a "machine voice" however, is boring

автор: Deleted A

17 окт. 2019 г.

Good start for someone trying to understand data science as subject

автор: Mynu a s

21 авг. 2019 г.

Need to explain more command and details of other option from tool

автор: Lucicleyton H d F

2 июля 2018 г.

Very good introduction to the tools widely used by data scientists.