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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: 32,682
Рецензии: 6,973

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:

6301–6325 из 6,863 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Andrew V

22 февр. 2016 г.

This course is very basic for a person with an IT background, but nevertheless might come in handy for people without relevant experience.

автор: Elbert B

16 сент. 2021 г.

G​ood overview intro, but assignments only measured that you were listening, they did not require applying content to any new challenges.

автор: Jaume A

22 июня 2020 г.

Difficult to follow the robotic voice at a speed of 1,5; the links simply don't workAnd, known bugs on LaTeX need to be found by googling

автор: Aishwarya K

25 янв. 2017 г.

There is a slight lack of clarity in videos in terms of audio and also in terms of what exactly the author/lecturer is trying to convey.

автор: Raneem Y

29 июня 2020 г.

thank you for the course it was useful. However the machine voice is really annoying and make fell uncomfortable and unfocused all time

автор: Siyang N

5 дек. 2020 г.

Course content meets the standard. However, the computer voice is really terrible. I suggest you switch back to human voice teaching.

автор: C. M B

7 сент. 2017 г.

It's a very basic course and easy to get through. I wish that they wouldn't make you wait to get to the next section of this series.

автор: Oliver K

19 окт. 2016 г.

Gives a good overview of topics and the specialisation, however is still very basic. I'm looking forward to the next advanced courses

автор: Matt S

14 мая 2020 г.

Some of the information for this course seemed to be missing and I felt I had to either guess a lot or search the internet for help.

автор: Alejandro S

17 мая 2016 г.

Good as just an introduction to data science. Some more exercises using Github, maybe some collaborative works would have been nice.

автор: Pedro H C C d A

21 мая 2020 г.

The "robot voice" speaks really fast making me having trouble to understand the content several times. Overall it's a great course.

автор: Ioannis V

31 дек. 2017 г.

gives some good information but the git section isn't really well made and it could have some improvements on sound and quality

автор: Brandon D

16 февр. 2017 г.

Very basic overview of the tools and installation of them. Should be an optional course rather than part of the specialization.

автор: Baktygul A

9 июля 2020 г.

Peer-review assignment questions leave out some assumptions; it took me a while to figure out what exactly was expected of me.

автор: Anmol A

25 июня 2018 г.

This course was a beginner level course and the difficulty level was quite low and in depth detail should have been provided.

автор: David R

4 сент. 2017 г.

Extremely basic, should likely be a pre-req for non CS/IT types but could easily be summarized for more experienced students.

автор: Lluís G

2 сент. 2016 г.

It is a good introductory course, but it could be optional for people with some experience in the field, as it is very basic.

автор: Alberto G M

8 февр. 2016 г.

The real basics of data analysis. The course is not bad I would just say it may be too simple even for an introductory course

автор: Rajeev J

15 сент. 2018 г.

Didn't get an awful lot from this course. The videos have a lot of information which are not directly related to the course.

автор: Bob D

5 февр. 2016 г.

This is a good introductory course to some of the tools but it doesn't go into the details of R programming or Data Science.

автор: Чмуров М В

21 сент. 2019 г.

не представляет ценности в качестве отдельного от специализации курса. весь курс является просто введением по специализации

автор: 현 허

22 дек. 2017 г.

It was too short and too easy, even though I didn't know how to use git. Only thing I learned is how to use git and github.

автор: Yuchen Z

26 мар. 2016 г.

Only include very basic contents, doesn't need 4 weeks to finish this course. More like a one or two day induction session.

автор: Marie-Morgane P

4 дек. 2016 г.

Basic introduction to the specialization. It was way too simple for me since I already have knowledge in machine learning.

автор: Calvin K

10 дек. 2019 г.

Please get rid of robot voice, it's awful.

Aside from that, very helpful and informative for preparation in other courses.