Chevron Left
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: 31,964
Рецензии: 6,819

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:

201–225 из 6,689 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Veera V k

7 дек. 2019 г.

Even though it is a starter course to the specialization learned so many new things like amazon polly which is being used to generate these videos, R-markdown and how important is it to produce reproducible research.

A must take course for any data science aspirant

Happy Learning!!

автор: Ting L

24 авг. 2018 г.

It's a great course for beginners. I had little knowledge about data science. I didn't even know what was R and GIt. After taking this course, I had a preliminary understanding of them. If anyone wants to learn data science without any experience, this one can be your start point!

автор: Tristan I

17 янв. 2020 г.

All the information felt applicable to my current role. The main thing I gained from this course is that I feel more confident in the tools at my disposal as a data analyst. Additionally I learned about tools I had never heard of & how to utilize them, and for that I'm thankful!

автор: Oskar D H

17 мая 2021 г.

Para conocer por primera vez Git y R, así como RStudio; y las implicaciones entorno a resolver un problema relacionado a la ciencia de datos, es un curso que lo hace de forma clara al explicar conceptos importantes para comprender el análisis de datos y hacerlo de forma optima.

автор: David L M

16 авг. 2020 г.

Good starting point for starting to learn data science. Short, practical course on definitions and tools for data science. I knew a little bit about R and RStudio (but not much) and didn't know anything about Git and Git Hub, and this helped me a lot to know these tools better.

автор: Dominic C

25 апр. 2016 г.

Great way to learn R and become familiar with how to use it. As a developer with an understanding of Python, Java, C and C++ I could quickly see how to use R, how to extend it and start working with it today. Very good use of supporting tools like Swirl to assist with teaching.

автор: Rodrigo E

23 окт. 2020 г.

I would prefer more courses with this format, videos and the reading section with exactly the same content, I have found that is better to read so you can go back to previous paragraphs if you didn't understand something. Both things are pretty good videos and reading section.

автор: Kaushal C

11 июня 2020 г.

The course provides a good introduction to the necessary toolbox required. It provides introduction to the Rstudio interface and Github version control system. The course helped me gain a lot of knowledge regarding Data Scientist toolbox, especially the version control system.

автор: Michael S

19 февр. 2018 г.

I found this course to be effective at getting the student to recognize the baseline set of tools, skills and behaviors expected in courses 2-10. Moreover, none of said tools, skills or behaviors fall outside the confines of typical and/or "in demand" experience. Nice work!

автор: parv s

5 мар. 2021 г.

The course material was in a structured manner and very easy to understand. One feedback I would like give is that there should be a form of one to one communication with instructors, so that students can clarify their technical doubts since this is a course based on coding.

автор: Prithvi M

11 мар. 2020 г.

Great course to get started with data science using R as primary language. Good data practices are encouraged and use of GitHub for version control gives additional confidence to anyone wishing to preserve their work that leads them up to the solution to the problem at hand.

автор: Francisco M R O

27 авг. 2018 г.

It's an excellent introductory course for the specialization, I have recommended this course to a friend because I have found the content pretty useful. I will continue with the other courses of the specialization and I'm very grateful to have this opportunity from Coursera.

автор: Oyetunde A O

13 авг. 2017 г.

This is a nice course and well taught by all facilities made available by the facilitators. As soon as am financially able to start to finish from where I stopped, I will activate my remaining course left to roundup Data Science Specialization.

I really appreciate. Thank you.

автор: Peres R B

3 апр. 2016 г.

Basic course introducing the minimum tools to start your journey in data science. The course was very important for me to get up to speed with Git and GitHub. All the information was given in a concise and objective way, yet covered all basic important points of such tools.

автор: Suryadeep D

17 мар. 2016 г.

Might look trivial at first glance to more experienced users, but was very much essential for a complete beginner like me. Gives a nice overview of a somewhat overwhelming (and sometimes intimidating) field and equips you with the basic tools necessary (like how to use git).

автор: Ashok K R K

27 февр. 2021 г.

Super insightful course, I was happy to get to learn to use version control systems. I would recommend it for everyone who is willing to get into data science. This course opens new set of possibilities and provides you the foundation needed to further advance your skills.

автор: Andrea P

3 сент. 2020 г.

Excelente curso, aumentó de manera óptima mis conocimientos y resolvió todas mis dudas, ahora tengo gran parte de las herramientas para llega a ser una buena cientifica de datos y aparte de que aprendí mucho sobre el tema, pude practicar el inglés y aumentar mi vocabulario.

автор: AKHIL K

11 апр. 2020 г.

The "Data Scientist's Toolbox" offered by Johns Hopkins University is a good head start for the newbies in the field of Data Science. The course gives the brief introduction to various software used by a Data Scientist that is R, R studio, Git hub and Git (version control).

автор: Nthabiseng M

8 янв. 2021 г.

I really enjoyed the course, the quizzes are very helpful because they taught me to listen and watch the videos carefully so that I can remember the content. As an IT student this course will be very helpful to me, and will open more opportunities for me in the ICT sector.

автор: Arthur D

11 апр. 2016 г.

Very good introduction to data science. It gives a general overview on data and its problematics but also tips and help on how to start with the basic tools that will be needed (I haven't done any R programming and didn't have a github account so that was helpful for me).

автор: Bhavay S

22 июля 2020 г.

It is a very good course to get introduced to the world of data science. Working knowledge of R, RStudio and GitHub is covered in a very nice and organised manner. I feel more confident and equipped to proceed further and learn how to solve problems through data science.

автор: Анатолий К

14 мар. 2019 г.

Интересно было посмотреть как работает один из лучших исследовательских университетов мира.

Кроме настройки программного обеспечения много узнал об основных принципах науки о данных.

Очень понравился пример с Хилари Клинтон. Возможно это был роковой момент в её поражении.

автор: Samuel W

8 июня 2020 г.

This is not a coding course. It is a course to bring you up to date with the logistics of using R: downloading packages, using RStudio, using GitHub version control, and familiarizing oneself with the overarching concepts of experimental design, statistics and big data.

автор: Hrishikesh P H

16 апр. 2020 г.

A very easy to understand, nice and simple course. ample quizzes and puzzles available. A recommendation : please include a thing or two about RStudio Cloud. Especially, please include how to tie up your github repo to RStudio Cloud; as the procedure s different for it.

автор: BHAGAWAT M

29 янв. 2020 г.

It's really enjoyable, a lot to know and a lot to discuss. The other links provided for more details are very much helpful. The feature of the discussion form is very helpful. Thanks, to Coursera and the team of Coursera for your high great work to open this platform.