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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

Оценки: 32,171
Рецензии: 6,875

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

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.

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:

4976–5000 из 6,759 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Marco A R

16 нояб. 2016 г.

Me pareció un buen curso introductorio donde conoces herramientas que se supone te ayudaran en tu carera como científico de datos

автор: vishal b

16 окт. 2016 г.

More number of hours are given than required. Good learning for non IT field people. For people with IT background, its too easy.

автор: Jon b

17 февр. 2016 г.

A little basic, but necessary to get everything you need set up for the next classes in the series. And it does that well enough.

автор: Surya P T

12 сент. 2018 г.

Good course and it's great that Coursera has designed this course separately.

Enjoying the journey of data science with Coursera.

автор: Alexandra D

28 июня 2016 г.

Would have bee nice if it included a bit more "in Git" tutorials, but that is easily figured out when left to one's own devices.

автор: Nica P

21 февр. 2021 г.

Great introduction to Data Science and useful tools. The AI voice took some time to get used to, but overall a good experience.

автор: Ivan A

24 авг. 2020 г.

The course provides a good theoretical basis to get into data science and it is also very practical to link github with Rstudio

автор: Elvis M M

1 июня 2020 г.

The introductory course is very helpful. Getting to know the use of Git and GitHub is very appealing and will be of importance.

автор: Martín S

30 дек. 2019 г.

Excelent, very clear. I only have problems with some changes in the versions of the programs. But fortunately I could solve it.

автор: A B C

26 июня 2017 г.

Great content for beginners, who actually need a start about what data science is all about and where it is used all around us.

автор: debashis r

8 февр. 2017 г.

Its a good course those who prefer to study online.It gives a basic knowledge about the data tools which are going to be used.

автор: Fabiana G

7 мая 2016 г.

I enjoyed the course - I wish there were more exercises, but hopefully they'll come in the next courses of this specialization.

автор: Matthew G

29 мар. 2016 г.

It covers some basics, but doesn't go deep into anything. Definitely take the other courses in the specialization to go deeper.

автор: xiang

17 мар. 2016 г.

Good courses and necessary for people like me who never have a relation to computer science,,, But it is a waste of

автор: Peter F

6 мар. 2016 г.

Very mechanical in nature. Worth doing though as it provides essential building blocks for the remainder of the specialisation.

автор: Jeanne R

10 июля 2020 г.

Very basic information but it does walk you through things quickly and clearly. The final project could use a little proofing.

автор: Claudia R C

29 мая 2020 г.

The course is well structured and it covers various concepts, but I think it could be enhanced with more practical activities.

автор: Ashutosh A

22 мая 2020 г.

The course is helpful to understand the basics of data analysis, big data, etc. more focus should be given to assignments in R

автор: Teresa E

30 дек. 2019 г.

This course is a basic conceptual introduction to data science and a glance at RStudio and Github. It is very easy to follow.

автор: Ian J A

8 окт. 2019 г.

Great course! However, the manuscript for module 4 is missing. Please fix as soon as possible to improve quality of lectures.

автор: Sorasa E

9 мар. 2019 г.

The content is amazing and easy to understand for the new student. However, the assignment question/instruction is confusing.

автор: Stuti M

14 мая 2018 г.

This is a short term starter for those willing to indulge in the world of data science. The course is crisp and to the point.

автор: Taimoor G

12 мар. 2018 г.

It's too easy for 1 month course.

Make it harder and make it shorter. Perhaps combine intro to R programming and this course?

автор: Graham C D

5 дек. 2016 г.

Great course to get you setup - don't expect to learn anything besides getting the correct software and file sharing profile.

автор: Hande K

26 мар. 2020 г.

Very useful course to start learning data science. Explains things clearly. Some explanations could have been more detailed.