Introduction to programming in Julia
Julia is a scientific programming language that is free and open source - see https://julialang.org/ for downloads, documentation, learning resources etc. Bridging high-level interpreted and low-level compiled languages, it offers high performance (comparable to C and Fortran) without sacrificing simplicity and programming productivity (like in Python or R).
Julia has a rich ecosystem of libraries aimed towards scientific computing and a powerful in-built package manager to install and manage their dependencies. Julia is also gaining ground in both data science and high-performance computing (HPC), thanks to a rich package ecosystem around data analysis and visualisation, machine learning, deep learning, threading and distributed-memory parallelisation, as well as GPU computing.
This lesson covers the basics of Julia: its syntax, multiple-dispatch paradigm, package development and best practices. It spans the necessary foundational skills required to follow the two other ENCCS lessons on Julia:
Experience in one or more programming languages.
Basic familiarity with a command line (terminal) interface.
Who is the lesson for?
This lesson is appropriate for researchers, engineers and analysts from academia, industry or the public sector who want to adopt a new programming language into their repertoire. It also represents the prerequisite knowledge to follow other ENCCS lessons on Julia - Julia for High Performance Scientific Computing and Julia for High Performance Data Analysis.
About the lesson
This lesson is developed by ENCCS - the Swedish node of the EuroCC network. It is open source and can be reused and remixed in derivative work; see detailed license information below.
Many excellent learning resources exist for the Julia language. For an overview, visit https://julialang.org/learning/.
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