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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: 33,075
Рецензии: 7,064

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


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.


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:

4951–4975 из 6,961 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Daniel P

8 февр. 2021 г.

It was a good introduction to RStudio and data science, however, the videos seems a bit fast for me to get every task done in par. The reading section after the videos helped me greatly.

автор: Huaxin W

18 мая 2018 г.

Very simple and easy-going. A good instruction to the very beginner of the data science and programming. If some topics could be discussed in a bit more details, I would more appreciate.

автор: Vivek I

15 дек. 2016 г.

The Data Scientist's Toolbox is a good introduction into Data Science specialization and gives a glimpse of what can be expected from the other modules. Looking forward to other modules.

автор: Vojtěch K

2 февр. 2016 г.

It is unfortunate that I was only able to audit this course and not take it for free without the Coursera certificate, as it is currently not possible for me to pay for the whole course.

автор: Alice W

24 янв. 2021 г.

Good stuff, though there are some changes I had to figure out as Github and other things with my Mac have slightly changed. (Though being a data scientist is about figuring things out)

автор: Yuvaraj A P

18 сент. 2020 г.

Good basic and well structured. What could have been better is the assignment and evaluation criteria. Possibly having result based evaluation would be better. Overall enjoyed learning.

автор: Ahmad A

24 апр. 2017 г.

greet efforts to learn us about Data Scientist's Toolbox, thank you very much

just one comment, it's about the instructor talking speed .. it was too fast and was not easy to keep focus.

автор: Yatin M

20 окт. 2016 г.

A gentle start to the 10-course data science specialization. Would not recommend taking the course just by itself. If you're planning on the specialization, it's a great way to easy in.

автор: William K

10 апр. 2018 г.

This is a good introduction the tools, however I had some issues with Git Bash and Git Hub, which was nor really answered in the lectures, could update the lectures with a live example

автор: Abdullah A

22 янв. 2021 г.

The course lacks the human part, since it is only a robotic voice, with no emotion and excitement.

But apart from that the course content was good and easy to follow for the most part.

автор: Nikhilendra M

26 авг. 2019 г.

The final assignment was really helpful in implementing what we learnt through the course. Some more details on the integration between Remote & Local folders would have been helpful.

автор: Xavier C

25 июня 2018 г.

Havegreatexpectationfortherestofthecurriculum.Visual presentations could be substantially improved, including the audio volume. But in general, great start down the Data Science path!

автор: Rajanikant T

31 авг. 2017 г.

This is just a basic overview into the world of data science. I would recommend only to the students just starting out in this field. Still, is a good course starting out. Have fun !!

автор: Fouzi T

12 авг. 2017 г.

Thanks to Johns Hopkins University for this helpfull course. It helped me a lot to understand the fondamentals of what data science is and the bueatiful tools used by data scientists.

автор: Ximena V

17 июля 2016 г.

All excellent and a very good introduction. I wish I was able to get my quiz graded without having to pay just to see if I was learning. For the rest, I recommended for a great intro.

автор: Pat S

21 апр. 2018 г.

This course describes the overview and useful tools for doing data science with less details. The material only prepare you for taking the other courses in the specialization track.

автор: Felipe K H

4 апр. 2017 г.

Overall the course is very good and well paced, but I believe it could be a bit more clear in the git and github lessons on how to push from your local repository to your remote one

автор: Stella L X T

30 мая 2020 г.

Not bad to start off with! It teaches installation of all the required things for starting off R (e.g. RStudio, GitHub), and gives a basic understanding of experimental design too.

автор: Javier A P O A

27 янв. 2020 г.

Al inscribirme en la especialización figura el español como uno de los idiomas en los que se dicta, pero no estaba disponible para este curso, por eso lo clasifico con 4 estrellas.

автор: Zili D

16 сент. 2018 г.

Great course. But sometimes it's a little bit difficult to follow, because the instructor just listed those Git commands without actually demonstrating how to use Git step by step.

автор: chad

8 сент. 2018 г.

I was already familiar with the stuff taught for the most part. I think they should do more tutorials on how to install and do things though for those not experiecned enough in it.

автор: James C

12 авг. 2016 г.

Good introductory course pointing to background reading materials and providing context for following courses as well as supporting the installation of the required software tools.

автор: Samin B

31 мая 2022 г.

T​his is a great introductory course to what it feels like to be a data scientist or analyst. It teachs the proper culture and etiquette carried out in the data science community.

автор: Debabrata G

25 апр. 2022 г.

The basics were well explained but the robotic voice is not engaging and I understand and appreciate the reason behind using it but further development in speech synthesis needed.

автор: fisica f

8 июня 2021 г.

E​s un curso basico para entrar en el mundo "Data Science" es imprecindible complementar este curso inicial con otros , sobre todo por que se necesita mas conocimiento con Rstudio