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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: 32,346
Рецензии: 6,906

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

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.

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.

Фильтр по:

4876–4900 из 6,791 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Shalini R

1 авг. 2020 г.

The topic covered in "Data Science toolbox" section covers the basics of data science, Installation of R. RStudio and Git.

It is nicely done and easy to follow.

автор: Chris S

19 дек. 2018 г.

I had prior limited knowledge of R and 'old' use of Git/Hub but this course offered a fast-track to refresh those skills in preparation for subsequent R courses.

автор: Allister G A

6 февр. 2016 г.

The course was very helpful and instructions were concise and easy to understand. Great for those fumbling around to scour the net for which tools to start with.

автор: Mohammed A E

16 авг. 2017 г.

A very good introductory course, However it requires a lot of personal research and reading to master the area, I believe more video excercises would be useful.

автор: chiuyuwen

16 янв. 2021 г.

That's great class. The way it explained is very clear. However the class is a bit basic for me. I was expected to learn syntax of R ect., but still a goo one!

автор: Moshiqur R

25 июля 2020 г.

I was very excited about this course, learned a lot. But, it became boring in the middle. Although, it was good considering the reading materials to back me up

автор: Wutikorn R

20 мая 2020 г.

It's a little bit boring, since you have to study a lot of toolbox without seeing them in actions for a few days. Best to watch at faster speed x1.25 at least

автор: Ornella S

19 апр. 2019 г.

The tutorial on github was not very clear to me, and the images used during the video and for the reading section were very blurry. Everything else was helpful

автор: Marcio C

17 авг. 2018 г.

A very superficial overview of the main tools used by a data scientist. Recommendation: The course could have more content. The quality of the content is good!

автор: Bhagya G

21 мар. 2017 г.

Helps install and set up the necessary software, but does require you to do bit of searching on the web to completely understand certain aspects of the course.

автор: nitika s

26 февр. 2017 г.

This Course is a great start for the specialization. The course is designed in a very thought manner so as to help a novice understand concepts easily. Thanks!

автор: Dev V

8 авг. 2016 г.

Nice course, sets you up with the basics for R programming, and sets you up with all the tools. Basic introduction to Git makes it interesting.

Overall, great.

автор: Dennis A

5 июня 2016 г.

Good introduction into basic data science tools and a nice starting point for the data science specialization. Yet, the certificate is a little bit overpriced.

автор: prateek l

12 июля 2020 г.

Good insight to the broad subject of R and analytics, only reservation if the video lectures could have been delivered by some person and not automated voice.

автор: Vaibhav S

3 мая 2020 г.

The course is well structured, but I still feel that it lacks human touch as the documents are read out by a program. Looking forward to learning new skills.

автор: Najlaa S

24 окт. 2016 г.

It was excellent course. I gained new information. I believe it need's hand on practice and base information for beginners who does not have any back ground.

автор: Asad R

2 апр. 2020 г.

Overall Content was good but I'm actually disappointed by the tone of the videos by some computer voice which actually makes it more difficult to undertsand

автор: Mohit G

16 янв. 2020 г.

Highly recommendable for beginners as you are going to get how to use the tools. I would recommend to go through this course before jumping to R programming

автор: Shivam J

24 мая 2019 г.

Covers all the basics. But yeah, just the very basics. Leaves a lot more to be learnt. I'm sure the upcoming courses in the specialization would be helpful

автор: Mauro S d S

5 мар. 2017 г.

It was good - I think I would like a bit more on Github, but it gets covered in other courses. It shall have more material on the coverage of data science.

автор: Vinoth K T

7 янв. 2016 г.

The introduction was very precise and straight to the core concepts of data science.

Please include a slide with the road map of becoming a data scientist.

автор: Filipe F

22 июня 2019 г.

Its a good basis. But i think there is a lot of information that is not relevant . Also, the materials of some questions are not mentioned in the videos.

автор: Mohamed A H A M

28 февр. 2019 г.

It is good as a start for a beginner, but I do not think it is adequate to be a separate course. Much of the material can be easily addressed in one week.

автор: WEI-LUN C

17 мая 2018 г.

It's a great course to have very basic introduction of Data Science.

In the meanwhile, also teach us how to install the necessary tool for future purpose.

автор: Christopher S

7 окт. 2017 г.

Not the most engaging material, but the course does a good job of covering the fundamentals of R and GitHub and helps you download the necessary software.