Welcome to the R Programming Environment

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The R Programming Environment

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Johns Hopkins University

The R Programming Environment

772 classificações

Curso 1 de 5 em Specialization Mastering Software Development in R

This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings. As the first course in the Specialization, the course provides the essential foundation of R needed for the following courses. We cover basic R concepts and language fundamentals, key concepts like tidy data and related "tidyverse" tools, processing and manipulation of complex and large datasets, handling textual data, and basic data science tasks. Upon completing this course, learners will have fluency at the R console and will be able to create tidy datasets from a wide range of possible data sources.

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Basic R Language

In this module, you'll learn the basics of R, including syntax, some tidy data principles and processes, and how to read data into R.

Welcome to the R Programming Environment1:54

Conheça os instrutores

Roger D. Peng, PhD
Associate Professor, Biostatistics
Bloomberg School of Public Health
Brooke Anderson
Assistant Professor, Environmental & Radiological Health Sciences
Colorado State University

Welcome to the course.

I'm Roger Pang,

a professor of biostatistics at the Johns Hopkins Bluebrook School of Health.

>> I'm Brooke Anderson,

an assistant professor of environmental epidemiology at Colorado State University.

>> So I'm really excited to teach this course because R has become just

incredibly popular, and

it's basically the defacto language for doing really sophisticated data analyses.

But in addition to being a language for data analysis, it's also this incredible

platform for building tools to kind of make your data analyses more efficient and

for kind of sharing your work with other people.

>> That's right.

In this course,

we're going to start off by giving people a tour of the R environment.

But then, we dig deeper into how to take your code and put it into functions, and

then to wrap those functions into packages.

And also, how to create data visualization.

>> Right, so I think in this first course,

we're going to talk specifically about kind of the grammar and the syntax of R.

We're going to talk about tools that are available for getting and

cleaning data, and kind of doing little data analyses.

And then we're going to talk about a bunch of other tools that are going to be useful

for as you kind of progress through the specialization, building packages and

writing functions.

>> Yeah, this course, we move kind of quickly through the basics of R.

So I think it's probably best for somebody either who has some R experience before,

or somebody who's coming in knowing how to program in another programming language.

>> Right, and so, just a little bit more about us.

So, I'm a professor here at Johns Hopkins.

My research focus is primarily on developing statistical methods for

environmental health problems, and I'm particularly interested in looking at

the health effects of indoor and outdoor air pollution exposure.

>> I study in environmental epidemiology and

do a lot of work looking into the health impacts of different climate-related

disasters, including heat waves and hurricanes.

>> So, we're really excited to teach this course, and

we're just really looking forward to seeing what you can build.

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