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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: 32,637
Рецензии: 6,964

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:

4851–4875 из 6,853 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Alina S T

12 сент. 2019 г.

I took the same course 6 years ago and it was a little more challenging. It actually had coding assignments. and not only in R, but in Python and SQL too. That was a more complex "toolbox"...

автор: Anoop B

3 мая 2020 г.

The course was excellent however the robotic sound of the AI was a challenge. Once I overcame my inhibition to learn from an AI system, I started to like the course and learnt a lot from it.

автор: Yitong L

9 июня 2019 г.

This course missed some important step, for example, the git push which is not be cleared how to push and does not teach us the git pull as the REANDME.MD is not in the local repo initially.

автор: Ashish K

8 дек. 2018 г.

Should spend a little more time explaining how interaction between Git and Github works. It is not very intuitive and requires revisiting the video as well as google search to understand it.

автор: Arjun S

27 авг. 2017 г.

A very easy course, can be completed in 3-4 days at max. Having done R programming course first, this was a breeze taking a couple days. Good for people starting off with the specialization.

автор: Sander H

25 апр. 2017 г.

What I like (so far) is that you have to search for information via internet and by practising your knowledge in GIT and GIThub you can discover what you have learned or what should improve.

автор: Manu B

10 окт. 2020 г.

The course was informative enough for the tools needed. But I think a separate course just for sake of knowing tools makes not much sense. I wish there was more in this course to implement.

автор: Demi

26 апр. 2017 г.

Some detail of the Quiz and course project were not mentioned in those video courses, it made me have to google or find out the answer in other ways. But through this, I did learned more .

автор: Samiksha S

29 июня 2020 г.

Good course for beginners to data science world.

However some more application questions must be added in each section to acquaint the learners with a thorough knowledge and understanding.

автор: Juan D M

20 окт. 2017 г.

Describe aspectos básicos para la utilización de herramientas, tipo de preguntas y datos que debe manejar un científico de datos; es un buen abre bocas para el resto de la especialización.

автор: Camila T J

14 июля 2020 г.

In generall it was a good course, but sometimes the instructions weren't sufficiently clear to me, and I had to figure things on my own which didn't always resulted in a positive outcome.

автор: Léa F

23 июля 2017 г.

Good introduction, although the teacher spoke in a very low voice (it was sometimes hard/impossible to catch what he said) and some of the videos could have been a little more exhaustive.

автор: Zach D

29 сент. 2016 г.

A nice slow intro to Coursera, but not a ton of actual content. Good to get your feet wet, but skippable if you are familiar with the basics of the toolbox or taking courses on Coursera.

автор: Daniel P

8 февр. 2021 г.

It was a good introduction to RStudio and data science, however, the videos seems a bit fast for me to get every task done in par. The reading section after the videos helped me greatly.

автор: Huaxin W

18 мая 2018 г.

Very simple and easy-going. A good instruction to the very beginner of the data science and programming. If some topics could be discussed in a bit more details, I would more appreciate.

автор: Vivek I

15 дек. 2016 г.

The Data Scientist's Toolbox is a good introduction into Data Science specialization and gives a glimpse of what can be expected from the other modules. Looking forward to other modules.

автор: Vojtěch K

2 февр. 2016 г.

It is unfortunate that I was only able to audit this course and not take it for free without the Coursera certificate, as it is currently not possible for me to pay for the whole course.

автор: Alice W

24 янв. 2021 г.

Good stuff, though there are some changes I had to figure out as Github and other things with my Mac have slightly changed. (Though being a data scientist is about figuring things out)

автор: Yuvaraj A P

18 сент. 2020 г.

Good basic and well structured. What could have been better is the assignment and evaluation criteria. Possibly having result based evaluation would be better. Overall enjoyed learning.

автор: Ahmad A

24 апр. 2017 г.

greet efforts to learn us about Data Scientist's Toolbox, thank you very much

just one comment, it's about the instructor talking speed .. it was too fast and was not easy to keep focus.

автор: Yatin M

20 окт. 2016 г.

A gentle start to the 10-course data science specialization. Would not recommend taking the course just by itself. If you're planning on the specialization, it's a great way to easy in.

автор: William K

10 апр. 2018 г.

This is a good introduction the tools, however I had some issues with Git Bash and Git Hub, which was nor really answered in the lectures, could update the lectures with a live example

автор: Abdullah A

22 янв. 2021 г.

The course lacks the human part, since it is only a robotic voice, with no emotion and excitement.

But apart from that the course content was good and easy to follow for the most part.

автор: Nikhilendra M

26 авг. 2019 г.

The final assignment was really helpful in implementing what we learnt through the course. Some more details on the integration between Remote & Local folders would have been helpful.

автор: Xavier C

25 июня 2018 г.

Havegreatexpectationfortherestofthecurriculum.Visual presentations could be substantially improved, including the audio volume. But in general, great start down the Data Science path!