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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: 30,951
Рецензии: 6,596

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:

4476–4500 из 6,453 отзывов о курсе Набор инструментальных средств для специалистов по обработке данных

автор: Uğurcan K

30 авг. 2020 г.

It's indisputable that topics in this course are so important to build a foundation for being a data scientist. The only problem I've faced is that the lessons are much slight. It should have given more details about topics.

автор: Atef A

17 нояб. 2020 г.

The course is well explained and give a great introduction to Data Science, but i would found it easier if the speed of instructions was slower and the tasks had more details in them to follow. In general, very good course.

автор: Jonelle C

11 сент. 2020 г.

Very easy to understand program, step by step helps a lot and the videos are actually very informative and helpful. I had a few problems with downloading and integrating Github into my Rstudio but it was easy to figure out.

автор: Zhao Y

21 окт. 2018 г.

got a general view of tools that data scientists need to know about or master. really useful and inspiring. this course encourages me to figure out problems I might meet during data analyzing like a data scientist. cheers.

автор: Lindtner A C

8 июня 2017 г.

it was hard to find to rewatch to git tutorials, as it was very fractured. Also, hated watching MAC tutorials to get all the vids done. Otherwise useful and well prepared material, looking forward for the rest of the spec.

автор: Sapna G

20 янв. 2017 г.

My first online course and it could not have been any better. Gives me the confidence that I can learn online and add to my knowledge new things. Course material was explained in simple terms which is not the case always.

автор: Carlos C

19 авг. 2020 г.

Good course to get you started on the Data Science Specialization from Johns Hopkins University. Maybe it could have had more weeks or more content, or at least more complicated exercises, but overall it's ok to start.

автор: Leah F

26 июня 2020 г.

I think the submission for the markdown file should be allowed to be EITHER an .md file OR an .Rmd file. Seems kind of silly to lose credit for pushing a .Rmd file directly from RStudio rather than saving a text file.

автор: Jeffrey G

30 мая 2017 г.

It was a fine overview. I think the suggested text was also okay, but for a $10 suggested price, I would say that there should either be a reading assignment or it should be made more clear that the text is optional.

автор: Álvaro S F

27 авг. 2020 г.

I wish I could listen to the professors' actual voices, because doing so in a more natural way would help me avoid tuning out from the lessons from time to time. But I fully understand why they are doing it this way.

автор: Nguyen N T A

7 июля 2020 г.

OK introductory course to the tools used by data scientists, however it's a bit odd this is a standalone course; IMO the course content isn't enough and should be combined with the next course in this specialization.

автор: Karen P

31 мар. 2018 г.

The class definitely eased a new learner who is unfamiliar with the concepts and skills. There are areas in this class that seemed outdated an made the class a bit confusing. Hopefully, those can be update in time.

автор: Karen H

10 мар. 2016 г.

This introductory course is a good overview, goes pretty quickly through the basics, and gets you prepped for delving deeper in the subject matter. Planning to sign up for the next course in this certificate program.

автор: Nick S

1 нояб. 2019 г.

This course was fantastic, I just wish that there was more interactive work within the lesson's versus only in the final project. I believe that would help the material set in faster and better. Overall good course.

автор: Delaram A

8 апр. 2020 г.

The content of the course was well-structured and useful. But unfortunately I could not use the videos very well. The robot voice was so annoying. I think the human voice is more soulful, pleasant and encouraging.

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 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.