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Intro to R

GRANT ROGERS - Monday, August 28
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R

as a statistical programming language, can help scientists and business experts harness cutting-edge techniques and work with large open-sourced resources by providing powerful data analysis capabilities, a vast collection of libraries and packages, and a thriving community for collaboration and knowledge sharing.

7) Dive into interactive R learning with swirl: swirl (https://swirlstats.com/) ↗) is an interactive R learning package designed to teach you R programming directly within the R environment. Install swirl in R and explore the variety of interactive lessons it offers. These lessons cover topics ranging from basic R syntax to data manipulation and visualization. Complete the lessons at your own pace and gain hands-on experience while learning R effectively.
 
 

1) Start by exploring the official R website: https://www.r-project.org/. ↗ It provides documentation, tutorials, and resources to get you started.

2) Join online communities and forums dedicated to R, such as the RStudio Community (https://community.rstudio.com/) ↗) or the rstats hashtag on Twitter. Engage in discussions, ask questions, and learn from experienced users.

3) Participate in R meetups, workshops, or conferences happening in your area or online. These events offer opportunities to network with experts, share knowledge, and stay updated on the latest advancements.

4) Follow influential R bloggers and thought leaders who regularly share insights, tutorials, and R-related news. Some popular R blogs include R-Bloggers (https://www.r-bloggers.com/) ↗) and Revolutions (https://blog.revolutionanalytics.com/). ↗.)

5) Explore open-source R packages and libraries on platforms like CRAN (Comprehensive R Archive Network) or GitHub. These resources offer a vast collection of tools and functionalities that can enhance your data analysis and modeling capabilities.

6)Consider taking online courses or tutorials specifically focused on R programming. Websites like DataCamp (https://www.datacamp.com/) ↗) and Coursera (https://www.coursera.org/) ↗) offer R courses taught by experts in the field.

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