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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: 32,149
Рецензии: 6,869

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:

4926–4950 из 6,751 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

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.

автор: Saleem G

17 апр. 2020 г.

I didn't like the computerized voice. The computer spoke a bit too fast and mispronounced some words. Certain sections went too fast.

автор: sachindra p

25 авг. 2019 г.

Overall the course is very good. However, I feel that a little more on statistics foundation would have added more value to the course.

автор: Rubens R

29 апр. 2017 г.

The content is very useful for beginners. Moreover, the material is very good, nevertheless the links target in PDFs cannot be reached.

автор: Dimitrios G

2 мар. 2017 г.

While this course is introductory to a specialization, I believe there is more curriculum that should have been covered in this course.

автор: jaclyn

11 июня 2020 г.

Helpful set-up course. Not too meaty & definitely didn't take 4 weeks but smart to have everything set up before diggin into the rest.

автор: Samavedam M P

1 июня 2018 г.

Good beginner's course to start learning advance topics like R programming, etc. Very useful tools such as Git-hub were taught simply.

автор: Arti

16 апр. 2018 г.

Very basic stuff - if you've ever done any coding before & have even a rudimentary knowledge of Git/Github - you can skip this course.

автор: Ennio D L

21 нояб. 2017 г.

Una introducción interesante y valiosa para los interesados en incursionar y tener a la mano las herramientas básicas de Data Science.

автор: Manasvita J

7 мая 2017 г.

A broad overview of a vast subject. It gives its students a good platform to get started on learning the nitty-gritty of Data Science.

автор: Vijay P

17 апр. 2017 г.

Gives an excellent overview to Data science course and what it take to become a Data scientist. Well organised videos and instructions

автор: Diana R

14 июня 2021 г.

AI voiceover isn't the best but I understand why it's used. On the heavier sections it would mispronouce commands and go too quickly.

автор: Enrique E

11 мар. 2021 г.

When describing steps to follow in R studio, or to link to Github, the video is impossible to follow, and the wirtten form is better.

автор: Marc-Antoine G

19 апр. 2019 г.

Pretty basic (from a software developer perspective) but can see the utility for newcomers to programming and informatics in general!

автор: Suwei W

7 окт. 2018 г.

This is my first data science class. I learned something about the tools, hopefully I will find them useful in the following classes.

автор: Gregory R B

19 июня 2016 г.

Good, but would like a step by step walkthrough for MAC/Windows when setting up the final assignment to ensure everything is correct.

автор: Krishna C T

21 мая 2016 г.

Good Introductory Class, all though I think some of the videos were too fast. Need to provide more explanation on some of the slides.