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.
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Об этом курсе
Карьерные результаты учащихся
34%
32%
Чему вы научитесь
Set up R, R-Studio, Github and other useful tools
Understand the data, problems, and tools that data analysts use
Explain essential study design concepts
Create a Github repository
Приобретаемые навыки
Карьерные результаты учащихся
34%
32%
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Университет Джонса Хопкинса
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Программа курса: что вы изучите
Data Science Fundamentals
In this module, we'll introduce and define data science and data itself. We'll also go over some of the resources that data scientists use to get help when they're stuck.
R and RStudio
In this module, we'll help you get up and running with both R and RStudio. Along the way, you'll learn some basics about both and why data scientists use them.
Version Control and GitHub
During this module, you'll learn about version control and why it's so important to data scientists. You'll also learn how to use Git and GitHub to manage version control in data science projects.
R Markdown, Scientific Thinking, and Big Data
During this final module, you'll learn to use R Markdown and get an introduction to three concepts that are incredibly important to every successful data scientist: asking good questions, experimental design, and big data.
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Основные моменты
Лучшие отзывы о курсе НАБОР ИНСТРУМЕНТАЛЬНЫХ СРЕДСТВ ДЛЯ СПЕЦИАЛИСТОВ ПО ОБРАБОТКЕ ДАННЫХ
Great course for a beginner. But, since I knew most of the content from previous works, there was not much new learning for me. I am confident the later courses will enhance my knowledge a great deal.
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.
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.
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.
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Что я получу, оформив подписку на специализацию?
Is financial aid available?
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