Historically, scientific and analytical programming has favored the use of dynamic languages like Python or R, which can often bring performance issues along with them. This is an unfortunate tradeoff, since these sorts of applications often have performance goals of the highest caliber. Julia, a relative newcomer to the programming scene, is an optionally-typed, LLVM-compiled toolchain that looks to offer the best of both worlds.

In this presentation, we will take a look at the world of Julia, from getting started with Julia to exploring the syntax, to some of the more interesting and powerful features of the language that may make it interesting even to those outside the scientific domain.


Slides: HTML | PPTX


Published on 25 April 2024