A tutorial will take place in a hybrid mode on the 20th of August 2025. Details to access in person and online will be provided in due course.

Prof. Mattias Villani, Stockholm University, Sweden.
Email: Contact

Description:

Julia has emerged as an important language for statistical data analysis and machine learning. It is a high-level language that is easy to learn, but with a speed close to C/C++ from its just-in-time compilation. Despite its relatively young age, Julia already has an impressive set of libraries for statistics, and can be easily integrated with a workflow in R or Python.

This tutorial introduces the Julia programming language and its use for statistical analysis. Participants are encouraged to install Julia and some statistical packages before the tutorial, to follow along on their own laptops. More details with installation instructions will be posted as we approach the conference.

The following topics will be covered in varying levels of detail:

• introduction to the Julia programming language
• the package manager and tooling
• managing data in Julia
• plots for statistics
• statistical distributions
• likelihood inference using numerical optimization
• using R/Python code in Julia, and Julia code in R/Python
• probabilistic programming for statistical inference using Turing.jl