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

Оценки: 32,171
Рецензии: 6,875

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

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.

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.

Фильтр по:

5001–5025 из 6,765 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Sorasa E

9 мар. 2019 г.

The content is amazing and easy to understand for the new student. However, the assignment question/instruction is confusing.

автор: Stuti M

14 мая 2018 г.

This is a short term starter for those willing to indulge in the world of data science. The course is crisp and to the point.

автор: Taimoor G

12 мар. 2018 г.

It's too easy for 1 month course.

Make it harder and make it shorter. Perhaps combine intro to R programming and this course?

автор: Graham C D

5 дек. 2016 г.

Great course to get you setup - don't expect to learn anything besides getting the correct software and file sharing profile.

автор: Hande K

26 мар. 2020 г.

Very useful course to start learning data science. Explains things clearly. Some explanations could have been more detailed.

автор: Adam D

22 авг. 2019 г.

Good overall. It would have been helpful to have more context or examples for the modules on version control and R Markdown.

автор: Deleted A

10 авг. 2016 г.

Great course that allows an introduction into the world of the data scientist. Some instructional videos could be improved.

автор: Melinda T

29 мар. 2016 г.

Good course. Short and sweet. Nice to be able to access future weeks' lessons and finish ahead of schedule if you wish to.

автор: Dr. A R

7 июня 2020 г.

Amazing and very simply going course. Learnt the basics of Rstudio and GitHub in a very simple manner. Thank you organisers

автор: Susan S

18 мар. 2020 г.

Great introductory. Some of the instructions were a bit vague at times - instructions RE code could have been more precise.

автор: ANKIT N

2 янв. 2019 г.

Course is in simplified way. student can easily understand the whole course. Makers made best efforts in making this course

автор: Qing Y

4 сент. 2017 г.

The quiz is mostly so'm'ething about the history or cha'ra'c'te'ristics of R or something else. No much knowledge provided.

автор: Srikanth S

27 мая 2017 г.

Was a great introduction. However, i felt, some of the lectures was very fast and i had to pause it constantly to try out..

автор: yaw o a

2 янв. 2017 г.

Quite a fast course. Material is a lot though and would be quite daunting for someone completely new to this sort of stuff.

автор: Ada

14 нояб. 2016 г.

I found the way in which John Hopkins present the course, very valuable. Well structured, although the pace is quite fast !

автор: Luis C H

13 сент. 2016 г.

Maybe too easy for some people, but is ok to ensure a minimum level in order to enroll other courses in the specialization.

автор: Bijan S

30 янв. 2016 г.

Well. I don't think this could be categorized as a course. You can think of it as table of content for the specialization.

автор: ankit g

17 мая 2020 г.

good for all those who want to start from scratch, but if you know R programming then it has no use for you except GitHub.

автор: Kris H

7 июня 2019 г.

Much of this was review material, but the structure was such that it would be effective for learning as a first-time user.

автор: hoo y s

24 апр. 2016 г.

a brief and yet organized and good resource for review old skills i have learnt and new skills that can acquire from here.

автор: Jason B

21 апр. 2020 г.

A great little course for anyone who, like me, is curious to know if data science is something they might want to pursue

автор: Deleted A

9 апр. 2020 г.

I thought it was good until Week three. I found some of the directions on how to download/set up programs very confusing.

автор: Francisco J A O

30 янв. 2020 г.

Really gets me, so I renew my interest in learning new things, It´s a well implemented course to introduce you to RStudio

автор: Deepak J N

6 авг. 2017 г.

It forms the base. The examples should be recent and since its more from Bio stats etc, sometimes gets a bit confusing. .

автор: Deleted A

2 мар. 2017 г.

This is a very good introductory course for all those who are eager learn about Data Science. It gives you good insights.