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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: 31,936
Рецензии: 6,813

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:

4901–4925 из 6,685 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Saruul A

18 дек. 2017 г.

very quick course just to get your workspace set up; if you are already familiar with github or rstudio, no need to check the videos

автор: John F

13 сент. 2017 г.

On our way to the Data Science certification. Nicely structured format and presentation of lectures, tasks, supplementary material.

автор: Damon G

8 мар. 2017 г.

Things got a bit hazy when it came to adding the .md file to our data science repo on GitHub. Other than that I enjoyed the course.

автор: Hanqi Z

12 июля 2017 г.

This is generally speaking a good course. The only problem is that the instructions are sometimes not detailed enough for beginners

автор: Avinash P

24 июня 2016 г.

A great starting. Perfect for providing a foundation. However, instead of slideshow, a few real-time videos would have been better.

автор: sachinkumar

7 июня 2016 г.

This course has given me a basic knowledge of different tools and statistical techniques that data scientist use to play with data.

автор: Moemen A

5 мар. 2016 г.

An essential introduction to the rest of the specialization program, but not too much information included in the course by itself.

автор: Danny N

19 июля 2021 г.

A great introduction course to the world of data science, Github and R programming. Easy for a beginner like myself to understand.

автор: Katherine H

4 янв. 2021 г.

This was a great course to get set-up and an initial introduction to all the important programs and software that interact with R.

автор: Ansh M

30 нояб. 2017 г.

The introduction to Git and GitHub could have been a bit less theoretical and more practical. Overall, a good introductory course.

автор: Jingfang

3 июля 2017 г.

I hope the content of this course would cover more materials during lecture. But overall, I am very happy with this course so far.

автор: Ritu T

6 нояб. 2016 г.

Ideal course to get you started for a data science specialisation. Informs about and helps you install all the required softwares.

автор: Vinay

1 июня 2016 г.

Overall, I liked being exposed to Github and GitBash. I felt this course gave me a broad overview of what to expect in the future!

автор: Umair A K

8 мая 2020 г.

Even though the content was good, but this is more like a 2 week course. I finished it in 4 days spending on average 1 hour daily

автор: Kumari N A

21 мая 2017 г.

If you are completely new to Data Science, then this is very good course to start with. All the basics are explained very nicely.

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.