To be held on Tuesday 17 November 2015 in Sydney and proudly sponsored by the ARC Centre of Excellence for Mathematical and Statistical Frontiers (

Julia is a new high-performance dynamic language for technical computing. Its central aim is to solve “two language problems”, whereby an initial program is written in a convenient dynamic language but then the computationally demanding parts need to be re-written in a lower-level language. By heavily exploiting features such as just-in-time (JIT) compilation and multiple dispatch, Julia is able to achieve performance comparable to statically-compiled languages such as C or Fortran yet have the convenience of a dynamic language such as Python or R. Julia is open source and freely available under a permissive MIT licence.

The aim of this course is to provide an introduction to Julia that would be of interest to statisticians. It will provide a solid introduction to the syntax and core ideas to the language such as types, generic functions and macros, as well as general guidance for writing high-performance code. It will then aim to cover some of the features that are likely to be of interest to statisticians such as statistics libraries, plotting and graphics functionality, as well as interfacing with other languages such as R, Python and C.

The course is primarily aimed at those who have some programming experience in a similar high-level language such as R, Python or Matlab.

The course instructor, Simon Byrne received a Bachelor of Commerce/Bachelor of Science in 2004 and a Bachelor of Science (Honours) in Mathematics in 2005 from Macquarie University. He has worked in the insurance industry and completed his PhD in Statistics at the University of Cambridge in 2011. He is currently an EPSRC Research Fellow in the Department of Statistical Science, University College London.

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