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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: 31,555
Рецензии: 6,703

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:

4926–4950 из 6,564 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Abhinay R

26 мая 2016 г.

A very good intro course but must be priced lesser when compared to the other courses in the specialization.

автор: Seung J L

8 февр. 2021 г.

Some of the material could be updated even more, but in general a good intro to a data scientist's tookbox.

автор: mohamed y

11 апр. 2020 г.

Great introductory to the data science tool box and its usage and benefits __ data science 0 course really

автор: Miryam A M C

10 февр. 2020 г.

Algunas partes del curso deberían tener mas ejercicios para practicar lo visto y reforzar mas lo aprendido

автор: Dushyant B

4 мар. 2017 г.

A good course to set up your software tool kit before you start your dive into Data Science Specialization

автор: Ihab A

13 июля 2016 г.

This course is perfect for really newbie. However, it also answers the question of "What is Data Science?"

автор: harish s

1 дек. 2020 г.

Good and clear explanation. if more assignments were given for practice, to would have been more helpful.

автор: Meagan V

13 апр. 2020 г.

Easy to follow for the most part. A couple of things were outdated so I had to figure them out on my own.

автор: Chen S

29 дек. 2019 г.

the course omits some important things like how to download MikTex and how to use it to open an rmd file

автор: Anku N M

9 янв. 2019 г.

Course was good, but would have been nice to have some TA/professor oversight of the discussion forums...

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).