R is a free and open-source statistical programming language that has become the norm in several data science fields thanks to its rich packages ecosystem. It is however a slow language with high memory usage.
People interested in training deep learning models, running computations on massive datasets, or carrying out large numerical simulations would be better off turning to faster languages such as Python with Numba or JAX, Julia, or Chapel—all of which we also teach.
For those who are already R users though, with computations that are not monstrous but take longer than seems reasonable, this course will cover benchmarking, various forms of optimizations, and several parallelization techniques. You will also learn how to run R on the Alliance supercomputers efficiently.