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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: 31,502
Рецензии: 6,696

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:

6476–6500 из 6,552 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Corey H

26 июня 2016 г.

In my opinion, most of this information should be free and available as a pre-req. for other classes (installing R Studio).

It was cheap, but in general, I thought I was going to be more out of this course than I did.

автор: YOGESH R

16 сент. 2020 г.

Students generally move towards online course to hear a human explaining them those concepts. This new technique may be time saving for you but it was really annoying and unexpected (almost everything )

автор: Ryan P T

20 авг. 2016 г.

$40 is way too much to spend just to learn how to install a couple pieces of software and sign up for a GitHub account. The entire course should have been the first week of the following course.

автор: Aayush L

20 сент. 2016 г.

Is this a real course for a data scientist just installing shit and a peer reviewing for that screenshot and forking all repos ...very bad not worth to be with rest course in specialization

автор: Diana K

20 мая 2019 г.

Good time of day! This course is great! But I can't finish it as I missed deadlines and can't switch session!!! I missed 1 month already because of this bug:(

It's so frustrating...

автор: Sebastian S C

10 апр. 2020 г.

Me inscribí en el curso y solicité una ayuda económica porqué supuestamente se dictaba en castellano. Pero esto no es cierto y no puedo avanzar. Por eso mi calificación en baja.

автор: Pablo A

15 февр. 2016 г.

Too basic content.

I have not learned anything with this course (installing R and RStudio should not be part of exercises or lectures).

I hope R programming course will be better

автор: Mahesh K

15 сент. 2020 г.

This is pure theoretical course,

It's look like a Power Point presentation. Students can not easily understand this.

I do not recommend this type of teaching on Coursera

автор: Joao P P

12 мая 2016 г.

Some interesting concepts, but way to simplistic in my opinion. Only reason I see to pay for it is the fact that it is a requirement in the Data Science Specialization

автор: Charlie Z

8 апр. 2019 г.

Do not take this course if you want to get a job in industry. Python now dominates industry and R is basically obsolete. I will be switching to a course in Python.

автор: Jonas L

20 мар. 2016 г.

Certainly not worth paying for this course, only talks about how to install the tools.

Not able to take quizzes when you try to take the course for free.

автор: Rajat J

14 мар. 2016 г.

Good introductory course. However, an overkill as a separate course (and hence charging $30 for it). Courses 1 and 2 could have been clubbed together.

автор: Isaac A G

23 апр. 2016 г.

It has almost no content and isn't actually useful. I've heard later classes in the series are way tougher, so the ramp up isn't at all good.

автор: Chris M

13 февр. 2016 г.

Not really enough content to be a course in it's own right, should be additional material as is useful, but definitely not a requirement.

автор: Attila T

24 янв. 2016 г.

It is really basic course, I expected much more even if this is offered only for $29.. (the cheapest course in the specialisation)

автор: Wei D

29 апр. 2020 г.

I think a few people like to hear the mechanical voice. Some videos have really low resolution and it is hard to see the codes.

автор: Marcelo X d N

25 дек. 2017 г.

Eu achei o site desorganizado, não sei se concluí ou não o curso. Não sei se executei todas as tarefas ou não. Decepcionante

автор: Valentin D

19 янв. 2016 г.

Completely useless. Just a number of boring videos of what you may possibly learn in Data Science Specialization.

автор: Francisco S

27 мар. 2016 г.

Not worth the price. Extremely basic stuff spread very thin over too much time just to be able to charge for it.

автор: Gianluca M

9 июня 2016 г.

Useless. The information content is close to zero. Just some blah-blah and a long tutorial to install software.

автор: Luke S

4 июня 2016 г.

Way too basic for the price - almost no content - this is just setup - I resent paying for setup instructions.

автор: John B

11 нояб. 2018 г.

Horrible explanation regarding push and pull requests. Would not recommend this course to my friends.

автор: Gary N A

8 мая 2017 г.

Poorly organized. Poorly communicated. No reliable source of assistance with technical problems.

автор: Stefan S

31 окт. 2020 г.

Would wish this course was not a requirement for specialization. Easy, and not giving anything.

автор: Omar A

22 июля 2020 г.

An online non-credit course authorized by Johns Hopkins University and offered through

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