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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: 30,997
Рецензии: 6,603

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

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.

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.

Фильтр по:

5126–5150 из 6,460 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Sohaib A

25 апр. 2020 г.

Great course but more stuff about R Programming makes it perfect.

автор: Anies v T

20 июня 2019 г.

One instruction-video was not working, but the text was avalable.

автор: Alejandra M R

25 июля 2018 г.

More instruction regarding Git on Mac would be extremely helpful!

автор: Radhika G

10 июля 2018 г.

Week 3 should be more detailed . What they are trying to explain,

автор: Divya N

30 июня 2018 г.

Pretty descriptive for beginners who do not have basic knowledge.

автор: Dave K

1 июня 2017 г.

Great intro class. Some boring lectures if you already know Git.

автор: Ronnie D

4 мар. 2017 г.

Good course! Lectures are easy to follow, have good instructions,

автор: Stefanie H

9 дек. 2016 г.

Good course; homework exercises are not particularly challenging.

автор: Patrick S

1 окт. 2016 г.

Good course stuff. A little bit too fundamental for a programmer.

автор: Gaurish S

10 авг. 2016 г.

should contain more tutorials about Git and GitHub functionality.

автор: HuDie落落

20 июля 2016 г.

It would be better if they are these practice teaching in detail.

автор: Mycal B

25 мар. 2016 г.

Good course, but it needs to be more difficult and more in depth.

автор: Manohar E

25 янв. 2021 г.

This is good program to start getting knowledge in Data science.

автор: Germán A P J

11 июля 2020 г.

muy bueno, pero deberia estar tambien con subtitulos es español.

автор: SUVVARI P

30 мая 2020 г.

i have completed my course and not get my certififcate till now

автор: Raj T

25 апр. 2020 г.

I got to learn new things which made me do better in DataScience

автор: Abdul S

15 апр. 2020 г.

A good introduction for getting started as data scientist and R.

автор: kopila P

14 окт. 2019 г.

It's a good start for people who are really new to data science.

автор: Ying T L

2 окт. 2018 г.

Hope there could be more demonstrations of the use of the tools.

автор: Mike Y

17 сент. 2017 г.

Good starting point, tool download, etc. Like the online format

автор: Gautam D

24 янв. 2017 г.

Very basic but needed for people not introduced to R! Thank you!

автор: Yeshar H

24 окт. 2016 г.

I would've liked some practical assignments on using Git/Github.

автор: Francesca I

12 мая 2016 г.

I think you have to say more about git commands and their syntax

автор: Victor N C G

26 мар. 2016 г.

I expected more detailed use of Github - otherwise great course.

автор: Syed A H R

10 июля 2020 г.

Good But, I would prefer if a person teaches rather than a bot.