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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: 31,731
Рецензии: 6,750

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:

4976–5000 из 6,609 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Adam S

8 февр. 2017 г.

So far so good, Git was a bit difficult to get going but I'm excited to continue with the specialization.

автор: Michael M

30 янв. 2016 г.

A good course for identifying the field of data science and introducing the computing tools of the trade.

автор: Bernard O

22 янв. 2021 г.

A simple introduction to R and data science. You have given me the appetite to know more and learn more.

автор: Guillermo C P

23 июля 2020 г.

Sometimes beginners MAC's users get a bit lost due to many explanations are only for Windows environment

автор: Thomas Z Y

6 мая 2017 г.

Straightforward, and I know what to expect for the next few chapters with John H University. Thank you!!

автор: Filipe M

28 авг. 2016 г.

Good introduction to data science, however it should have more details and practical examples about Git.

автор: Eileen S

9 февр. 2016 г.

Super basic introduction. I liked the last section reviewing data science methods and conceptual ideas.

автор: Donghee L

31 янв. 2016 г.

I think more detail statements are needed on PDF.

Because I'm not good at listening, so I studied by PDF.

автор: Shriya I

12 авг. 2020 г.

Extremely informative & interesting, Instructions can be followed with ease. Worth the time and effort.

автор: John E F

4 дек. 2019 г.

Excelente curso, porem diferentemente da descrição, existe legenda em português, apenas para um modulo.

автор: Satya P

2 окт. 2018 г.

Structure, content and step by step practice was good. Interface to browse the courses could be better.

автор: Jay G

24 мар. 2016 г.

Good start, looking to dig in more, as I already have a background in stats data analysis and data viz.

автор: Vicent G

27 янв. 2016 г.

Quite simple. It could be more engaging.

When downloading PDF slides, links in them should be clickable.

автор: Cristiano L

11 авг. 2020 г.

Good and objective course. Gives the basics about data science and how to get started with R software.

автор: Brandon W

23 мая 2020 г.

Good course. I felt the Git course went a bit too quickly (and I have experience with Git and Github).

автор: Sanidhya S

21 дек. 2018 г.

Great cousre for starting in the data science since, it contains the installation and usage of tools .

автор: Danylo K

10 сент. 2018 г.

From the begining of the course thats difficult to catch structure if you are new to the Data science.

автор: Russ L

14 апр. 2018 г.

More direct examples would be nice. Kinda like what they do on Data School. Otherwise very well done!

автор: Aliaa M A

30 нояб. 2017 г.

Brief and Excellent! Content great for anyone getting into software development not just Data Analysis

автор: santiago R

30 июня 2017 г.

Nice Course. Important to have a general idea about what is necessary and also useful for data science

автор: Matthew S

5 сент. 2016 г.

great intro to stats concepts for data science and the programs. No real coding taught in this though.

автор: Victoria S

26 мая 2016 г.

Helpful for people with no experience on the subject matter. Very straight forward and easy to follow.

автор: Saul H

8 июля 2020 г.

Really good. Just some minor issues with the automated voice and some typos. All in all great though.

автор: Nivedh R

15 янв. 2018 г.

Good, simple introduction to the specialization. Accompanying PDF slides would be great if clickable.

автор: Siert A

3 нояб. 2016 г.

Very good introduction. It is a very basic, but much needed step. Setting up the tools you will need.