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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: 32,981
Рецензии: 7,045

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:

6426–6450 из 6,941 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Abdallh A

11 дек. 2019 г.

Good course for supporting the rest of the specialization. However, it has very little use on its own.

автор: M S G

3 февр. 2019 г.

Would have loved it even more if there was an in-depth explanation of how to use GitHub using Git bash

автор: Karan A

6 июля 2018 г.

Course is good overall, but it could be more detailed and informative which is lacking at some topics.

автор: Adriana M M V

29 мар. 2020 г.

Needs examples and practical exercises. The videos are long and monotonus mainly because the speaker.

автор: Sourav P

29 июля 2018 г.

One Could have introduced the basics of R in this course..The course was too easy..Even for beginners

автор: Hernan G

27 сент. 2017 г.

Es básico, pero cumple para empezar en el mundo de Coursera, espero mucho más del resto del programa.

автор: SOUBHAGYA K

1 авг. 2020 г.

It's very very basic one.Some more topics should be added to this course.Otherwise it will be boring

автор: Chia D

11 дек. 2019 г.

The video content is great, but it tends to have zero relation to the content tested in the quizes.

автор: Deepankar G

2 июня 2016 г.

Course doesn't seem to be of much use. Was not much informative. Only some information is relevant.

автор: Peter F

4 апр. 2016 г.

It was pretty good, but most of the information is rehashed briefly in the intro to R Programming

автор: Pavan E

14 февр. 2016 г.

Course was good, nice introduction to data science and its branches. There was not much of depth.

автор: Andrew R

12 мая 2020 г.

I don't feel like I learned a ton from this, but hopefully, it prepares me for the next courses.

автор: Hrishikesh T

9 мая 2020 г.

I didn't like the fact that the instructor didn't feel human-like, however, it felt more robotic

автор: Arun J

3 янв. 2019 г.

Content is not found sufficient. Also order of the video series also requires some modifications

автор: Bill H

28 мар. 2016 г.

A necessary prerequisite for the other Data Science classes, but not really a standalone course.

автор: Nath S

7 дек. 2021 г.

I liked it because it helped me to configured the software that I will use in the next courses.

автор: TESSIER B

13 февр. 2016 г.

Good overview of existing tools but more information will be useful to dig into the data world.

автор: leo0807

3 июля 2019 г.

I think maybe because I have computer science background, so I think this course is too easy.

автор: Nikita S

2 февр. 2018 г.

I don't really think that this amount of information should exist as a whole separate course.

автор: Lucio C

8 авг. 2016 г.

Good overview. But it is confusing for the first class when you have no idea about the topic.

автор: Bhupen P

22 июля 2021 г.

Need more practice in R programing, Github, commit, branching, adding text, making directory

автор: Maciej M

18 февр. 2018 г.

some information was interesting but in general I don't think it was crucial for learning R.

автор: Benny B E

1 авг. 2017 г.

If you don't know any thing about data science, good introduction, otherwise a wast of time.

автор: Yves-André G

27 мая 2017 г.

A very simple course, focussed on installing the correct tools on your computer to learn R.