Chevron Left
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

Оценки: 31,494
Рецензии: 6,695

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

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.

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:

5151–5175 из 6,551 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: GERARDO A P F

6 апр. 2021 г.

It is hard follow a robotic voice, but the information is clear enough

автор: SFA P

8 нояб. 2020 г.

For beginners, the github version control materials are hard to grasp.

автор: Carlos V

6 сент. 2020 г.

Buen curso, aunque incomoda que todo sea realizado por una voz digital

автор: Alberto H P

21 мая 2020 г.

Claro, fácil de seguir y bien secuenciado. Una buena introducción a R.

автор: Md A H

7 мая 2020 г.

this course is very helpful.i gather many new things from this course.

автор: gabriel h

24 авг. 2019 г.

Very good course, need a little update but has very easy do understand

автор: Jukka H

5 февр. 2019 г.

It covered the basics of concepts and tools that Data Scientist needs!

автор: Dolphin L

13 сент. 2018 г.

A good course. Step by step to create concept for git, github, R tool.

автор: Adit W

23 янв. 2017 г.

It was a good introduction. Looking forward to the rest of the course.

автор: Vijay S

21 окт. 2016 г.

Covers the basic effectively.Hope it's useful for the upcoming courses

автор: Mykela G

15 июля 2016 г.

This course is a very basic introduction, but I think it is an importa

автор: Jaheer H A

5 июня 2016 г.

Very excellent startup to motivate a one want to become data scientist

автор: Rodrigo G D V

26 янв. 2021 г.

Nice course, but I feel like I'm taking programming classes from siri

автор: 坂本幹次

26 авг. 2020 г.


автор: Kashif K

31 июля 2020 г.

It is very good course in a short time for all who love data science.

автор: Hani A

16 мар. 2019 г.

The course should be more interactive. It's such an exciting subject.

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!