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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: 33,152

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:

6501–6525 из 6,979 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Bhupen P

22 июля 2021 г.

Need more practice in R programing, Github, commit, branching, adding text, making directory

автор: Maciej M

18 февр. 2018 г.

some information was interesting but in general I don't think it was crucial for learning R.

автор: Benny B E

1 авг. 2017 г.

If you don't know any thing about data science, good introduction, otherwise a wast of time.

автор: Yves-André G

27 мая 2017 г.

A very simple course, focussed on installing the correct tools on your computer to learn R.

автор: Migdonio G

11 февр. 2017 г.

Too little material for 4 weeks. All this could've been written in a PDF instead of videos.

автор: Mark P

11 окт. 2020 г.

the computer voice is very hard to handle.

low production value of the course in that part.

автор: Kapeesh

26 июля 2020 г.

Video lectures where TTS, not at all engaging. Thankfully, text material was well written.

автор: Shahrooz

22 июля 2016 г.

Overall the course content is good, but the power points are not engaging and interactive.

автор: Mantra B

27 июня 2020 г.

Very Basic level. A little difficult to stay focused without having an instructor around.

автор: Sadanand U

19 авг. 2018 г.

Very basic, may be a bit more use cases on Git would have been useful. But that's just me

автор: Uian S

23 нояб. 2017 г.

Few content for an entire course. I think this one could be together with R Programming.

автор: Ali A F A N

12 апр. 2020 г.

Wasn't as good as I expected, but still I learnt from it, I can say it's above average.

автор: Andreas L

3 дек. 2017 г.

I am aware that this is the introduction to this topic but it was a bit long-drawn-out.

автор: Juan J E

22 окт. 2017 г.

I was already familiar with some content. it was a good starting point for may training

автор: Craig G

27 янв. 2017 г.

A good intro to the tools, but for anyone with prior programming experience unnecessary

автор: Debanjan D

25 мая 2019 г.

Okayish course. This course will give you an introduction in RStudio and Data Science.

автор: João P S

7 сент. 2017 г.

Too few activities for the time allocated. I completed this course in 4 periods of 2h.

автор: Danyal F B

7 июня 2017 г.

I think the project became very confusing since no examples were done in the lectures!

автор: Seckin D

20 мая 2016 г.

I think this class is best for academic people. I did not find what i was looking for.

автор: kheman g

5 авг. 2020 г.

This is a very basic of the course where I learned so much about the different tools.

автор: John Y

8 июля 2017 г.

This could be wrapped into one of the other courses since its just environment setup.

автор: Ryan C G

17 янв. 2017 г.

Pretty simple, the Univ of Michigan Data Science with Python set the bar pretty high.

автор: Ankush K

31 мая 2017 г.

A little boring. Necessary if you have ABSOLUTELY no experience with data analysis.

автор: Drake O N

17 мар. 2017 г.

Good starter setup. Looking forward to the technical portion of the Specialization.

автор: Yash D

24 мар. 2020 г.

the course is good but the language is little bit hard because it is auto generated