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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: 31,918
Рецензии: 6,808

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:

4851–4875 из 6,677 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Glauco P S

30 июня 2020 г.

I do understand why they used automated videos in order to keep all the material as updated as possible, however it is a strange experience.

автор: Judith W

2 апр. 2020 г.

It is a good course to get familiar with the basics, however, I would have liked a little more actual content. Week Four I enjoyed the most.

автор: Suryakant S

7 февр. 2020 г.

I liked the course as it helped me to understand the basics of R programming including the installation of R studio and linking it to GitHub

автор: Leul B

2 нояб. 2016 г.

Pretty great introductory course on types of data analysis. I can't wait to see how this builds in the future courses of the specialization.

автор: SantoshKumar

5 мая 2016 г.

Nice course for Beginners, No complains regarding course material, however there is little bit audio issue in some slides as it is bit low.

автор: Peter E

14 февр. 2016 г.

Great Course! Overall I would recommend. Had a little bit of trouble b/c I am using a Mac but after a few Google Searches I was on my way!

автор: Brandon P

20 янв. 2016 г.

Great course! I would recommend compressing the audio on the video presentations so it's easier to hear and more consistent in volume level.

автор: ashe g

28 апр. 2020 г.

This course is nice kick start for the upcoming courses but the course could have been even more interactive . over all nice experience .

автор: Kadimisetty H S P

12 янв. 2020 г.

This course helps many of us to get started with R and R studio. It also explains about some famous terms in data science and statistics. T

автор: Chloé S

23 мая 2019 г.

Everything was perfect except the Git and Github part. It was confusing. I ended up not using what it has teached me to pass the final exam

автор: Girish V V

28 дек. 2018 г.

Quiz in final submission related to usage of toolbox Rstudio, like loading new packages will add more value and will help the learners also

автор: Francesco M

28 дек. 2017 г.

Good introduction on Data science specializationi. I highly recommend to all people that would like to know more about this fantastic world

автор: John W

9 янв. 2017 г.

I knew most of the material in this course already, but I thought it was a good introduction to some of the tools that data scientists use.

автор: Olivera D

11 июня 2020 г.

The automated voice of the lectures is dehumanized. It is less productive and focusing learning from a machine, but the material was good.

автор: Zengqi L

7 мар. 2017 г.

I wish the instructors can be more clear with the Git and Github part. I still don't fully understand how to use Github for various tasks.

автор: RHR P

13 мар. 2016 г.

The course is very nice and provides all that you need to get started on Data Science. Looking forward to the next set of courses. Thanks!

автор: John T M

17 дек. 2020 г.

It was a good start and overview. The robot voice didn't always read correctly. RStudio has changeds since slides were made. Mostly good.

автор: Jonathan H

10 янв. 2020 г.

Material is awesome! Clear and simple, with great examples!

Questions at the end of the modules are confusing sometimes, could be improve!

автор: Syam P V

12 нояб. 2017 г.

Good crash course on setting up all the toolbox necessary for a data scientist. The quiz could be more difficult than it is designed now.

автор: Arthur G

13 февр. 2016 г.

In the course they use some tools' older versions and, for example, some Git commands shown on video are different in newer Git versions.

автор: Anand S

29 янв. 2016 г.

Informative and helps people like me who are willing to learn from scartch. The course content though can do with a little more updation.

автор: Tanjim R

16 апр. 2020 г.

This course is very good for introduction to Data Science toolbox . But there are some typing mistakes in the subtitles in some videos .

автор: Boris K

14 сент. 2019 г.

Простейший базовый курс, не требующий никакой предварительной подготовки и минимум усилий. Указано 4 недели, по сути проходится за день.

автор: Chris W

4 апр. 2016 г.

This was a very professionally done course. It is *very* introductory, which is either good or bad, depending on how you feel about it.

автор: Sichen L

10 июня 2020 г.

it introduces the basic tools that are frequently used in data science. However, it is rather baisc and the course did not go in depth.