Parallel Programming with R & RStudio: Complete Tutorial

R Programming, RStudio, Parallel Computing, Multicore, R for Data Science, R Speed Optimization

Created by: Arkadi Avanesyan
Consultant and Codementor

What Will I Learn?

• Understand core parallel computing concepts.
• Explore essential R packages for parallel computing.
• Implement parallel computing on multicore processors.
• Improve R programming script and data analysis performance.
• Apply parallel computing in practical RStudio data science projects.
• Learn to identify and resolve parallel computing issues.
• Follow coding best practices for reliable and efficient R programming.
• Analyze real-world examples of parallel computing in R and RStudio.

Requirements

• Familiarity with the R programming language is beneficial.
• A general understanding of data analysis in R is helpful.
• A computer or laptop with R and RStudio is optional.
• Enthusiasm and a willingness to learn R and RStudio.

Target audience

• Novice to Advanced RStudio Users: Individuals at various levels of R proficiency
• Professionals handling large datasets in business consulting.
• Beginners focusing on R programming before advanced topics.
• Data Scientists and RStudio Developers
• Excel Users Transitioning to R Programming
• R programmers exploring parallel computing.