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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: 29,852
Рецензии: 6,369

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:

4326–4350 из 6,230 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Mixalis K

21 мая 2017 г.

It was very exciting taking this class because i learnt about the conceptual ideas of data scince wich was my goal and the fact that i started using some data science tools also helped in understanding the issue

автор: José F E K

19 нояб. 2018 г.

I think it's a great course, but because it's the course on tools for a data scientist, it would be a more effective approach if it contained more information about many other tools used by those professionals.

автор: Morgan W

18 янв. 2016 г.

Good introductory course. Learnt a more structured approach to categorising statistical methods. Much of the rest of the content was a bit basic, though probably useful to fill in any knowledge gaps pre-course.

автор: Eryka W

12 мая 2020 г.

This was a very good overview of what a data scientist needs. The information was presented clearly and it was very helpful to do projects along with the seminars to start learning R, R Studio, and R Markdown.

автор: Muhammad B

28 янв. 2018 г.

Author was speaking to quickly, its was every difficult to understand for me as non-native English speakers. An other thing that i notice is that the error message was completely misleading. Should be improved

автор: Andrés C

5 окт. 2016 г.

It is very clear and useful course. It holds one hand to go sure through the contents. Anyway, I would suggest to end at certain point doing something simple in R, to give an end to this chapter in this story.

автор: Jing C

25 окт. 2020 г.

In this course you would learn some basic knowledge about R language, GitHub and how to use them. It is just a startup course. If you want to learn how to program in R, you should go further and learn deeper.

автор: Sandhya S

13 июля 2020 г.

I felt something in detail was required for GitHub and RStudio. There were repetitive questions asked. Those can be removed and only one question should be asked with repeating it in any of the questionnaire.

автор: Benjamin S M

28 июня 2020 г.

Simple and easy, but also essential information. This was a great course for beginners using R, R Studio, Git, GitHub, and for anyone who wants an introduction to data science, programming, and data analysis.

автор: Saloni R

20 мая 2020 г.

This course gave me a great headstart to step into the field of data science with more confidence. The lectures are very well created, scripted, and delivered using the Amazon Poly.

Overall a great experience.

автор: John S

14 нояб. 2016 г.

Very good pace, sequencing, and mix of lecture and practice. Only suggestion is a bit more time on the "Add", "Commit", which appears to be a very core element of file handling/version management with GitHub.

автор: Jiapeng S

14 нояб. 2019 г.

I used 7 days free trail first and then purchased it, then I found almost all the videos and works in free trail version are different from purchased version, can't understand why the institution did that.

автор: Baurjan S

13 апр. 2016 г.

The first week's quiz is really difficult and I had to go through the lecture material several times. Because of the great number of very short lectures it is difficult to find an asnwer to sought question.

автор: Julian M D C

26 апр. 2020 г.

The content in the course is very helpful as an introduction to Data Science. There is no enough material to 4-week study. I finished the course in 3 days at a regular pace. Robotic voice is a bit annoying

автор: Tales T d S P

16 мая 2016 г.

There were lectures about how to install R and RStudio on Mac and Windows. And the quiz asked about information on these lectures. You must pay attention to them even if you have previously installed them.

автор: Angie M

24 мая 2020 г.

Seems like the lessons are using an older version of R. BioConductor repo packages instructions need updating. Otherwise, this course gives a good intro to Data Science and how to use RStudio with GitHub.

автор: Vivian G

12 мая 2020 г.

This course gives you a nice overview of the very first steps in dealing with your data. It explains very well how to use GitHub and RStudio.

The mini-quizzes (3 questions) are a bit useless in my opinion.

автор: Pranali S L

22 июля 2020 г.

Course was Excellent . I have learnt many things from this course which will be very helpful in future .My suggestions will be -framing of questions should be more exact.,so learner will not be confuse.

автор: Luis C

17 нояб. 2016 г.

El curso tiene toda la orientación a ser la primera parte de toda la hoja de ruta de la especialización de data science... En solitario no aportará prácticamente nada pero como punto de inicio, promete.

автор: Wenting T

23 мар. 2016 г.

The course is in fact an overall intro to the full data science specialization. Some of the content are useful; but some of the quiz questions are not very informative, and don't really test on stats...

автор: Rose E

15 апр. 2020 г.

It would be nice to have the R Studio and GitHub training with more guidance and proper syntax and coding for both and I would prefer it after the R programming course. Otherwise, good content overall.

автор: Marcus F

13 апр. 2020 г.

Yeah, the robot voice is annoying. There needs to be better instruction on getting R Markdown to work. I tried in vain and gave up on it after looking at multiple forums with my same issue. Oh well.

автор: MADHUSUDAN S T

12 апр. 2020 г.

It's a beginning to a host of different courses that are to be followed after this. It makes up a for a good platform to start off the work on R and how to use version control feature of R via GitHub.

автор: Sumeeth R

15 мар. 2017 г.

It would be better if we can attempt the assignments even if we are not enrolled to the course. It would really help us to evaluate ourselves about the extent to which we have understood the concepts.

автор: Chris C

11 июня 2016 г.

A good basic class and collection of the tools. I wish there had been a little more explanation of what we would use the software for, but I found the lecture parts to be both concise and informative.