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DataCamp

Parallel Programming in R

via DataCamp

Overview

Unlock the power of parallel computing in R. Enhance your data analysis skills, speed up computations, and process large datasets effortlessly.


The R programming language is a crucial component of the modern tech stack, but R code can sometimes take time to execute. This course on parallel programming can help you optimize your code by leveraging the multiple processors found in most modern computers. You'll grasp key parallel programming concepts and identify operations that can benefit from parallelization. You'll also explore established R packages (parallel, foreach, future) for parallelization and acquire the skills to reduce execution time, monitor, debug, and ensure reproducibility in parallelized code.

Syllabus

  • Introduction to Parallel Programming
    • Learn to identify those pesky speed bottlenecks in your R code. You will run a classic numerical operation in parallel and learn to check if it helps!
  • Parallel and foreach
    • Use parallelism in R for a variety of situations while efficiently managing dependencies. Turn those slow loops into smooth-running machines!
  • Parallel Futures
    • Dive deep into the use of futures in parallel programming. Learn to process vectors, lists, and data frames in parallel, all the while keeping your code easy to maintain.
  • Troubleshooting in Parallel
    • Learn to manage memory for parallel processes. Make your code reproducible, and add efficient debugging to your parallel programming toolkit.

Taught by

Nabeel Imam

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