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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: 30,599
Рецензии: 6,520

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:

5051–5075 из 6,378 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Yhael S J C

4 июля 2020 г.

Interesante y algo para empezar que debería ser básico al aprender

автор: Ramkishore R l

11 июня 2020 г.

better experience and looking forward for more and more knowledge.

автор: Akshay N

24 янв. 2020 г.

Basic course. Didn't really enjoy the automated voice from Polly.

автор: Siddharth J

12 июля 2019 г.

It is a good course. Can include some more topics and explanation.

автор: Waldemar T

22 мая 2017 г.

Great introduction of subject matter. I'm excited to participate!!

автор: Giovanna A G

2 авг. 2016 г.

This course provides very nice and useful tools for data analysis!

автор: Thomas D

15 июня 2016 г.

Succeeds in conveying course prerequisites, contents and benefits.

автор: Robert d L

4 окт. 2020 г.

A good start to getting ready for the data science course proper.

автор: Muhammad S

25 апр. 2020 г.

Great course but more stuff about R Programming makes it perfect.

автор: Anies v T

20 июня 2019 г.

One instruction-video was not working, but the text was avalable.

автор: Alejandra M R

25 июля 2018 г.

More instruction regarding Git on Mac would be extremely helpful!

автор: Radhika G

10 июля 2018 г.

Week 3 should be more detailed . What they are trying to explain,

автор: Divya N

30 июня 2018 г.

Pretty descriptive for beginners who do not have basic knowledge.

автор: Dave K

1 июня 2017 г.

Great intro class. Some boring lectures if you already know Git.

автор: Ronnie D

4 мар. 2017 г.

Good course! Lectures are easy to follow, have good instructions,

автор: Stefanie H

9 дек. 2016 г.

Good course; homework exercises are not particularly challenging.

автор: Patrick S

1 окт. 2016 г.

Good course stuff. A little bit too fundamental for a programmer.

автор: Gaurish S

10 авг. 2016 г.

should contain more tutorials about Git and GitHub functionality.

автор: HuDie落落

20 июля 2016 г.

It would be better if they are these practice teaching in detail.

автор: Mycal B

25 мар. 2016 г.

Good course, but it needs to be more difficult and more in depth.

автор: Germán A P J

11 июля 2020 г.

muy bueno, pero deberia estar tambien con subtitulos es español.

автор: SUVVARI P

30 мая 2020 г.

i have completed my course and not get my certififcate till now

автор: Raj T

25 апр. 2020 г.

I got to learn new things which made me do better in DataScience

автор: Abdul S

15 апр. 2020 г.

A good introduction for getting started as data scientist and R.

автор: kopila P

14 окт. 2019 г.

It's a good start for people who are really new to data science.