Intro To Julia Lang
I am currently delivering a (three-part) short course in finite element analysis with Gridap at TurlierLab.
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs). It is 100% written in the Julia programming language.
The first session of the course was an introduction to the Julia programming language. The salient feature of Julia is that it does not force you to trade-off between code performance and code productivity. Thus, it is a worthy language for computationally-demanding scientific computing applications, such as finite element analysis.
If you want to learn more about Julia, you can take a look at the session slides. They contain a curated list of info and resources to help you migrate to Julia from C/C++, Python or any other language.
Delivering the intro to Julia session