Introduction to programming in Julia

Julia is a scientific programming language that is free and open source - see 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.

See also

Many excellent learning resources exist for the Julia language. For an overview, visit


The lesson file structure and browsing layout is inspired by and derived from work by CodeRefinery licensed under the MIT license. We have copied and adapted most of their license text.

Instructional Material

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