Julia is a modern high-level programming language that is fast (on par with traditional HPC languages like Fortran and C) and relatively easy to write like Python or Matlab. It thus solves the “two-language problem”, i.e. when prototype code in a high-level language needs to be combined with or rewritten in a lower-level language to improve performance.
Although Julia is a general-purpose language, many of its features are particularly useful for numerical scientific computation, and a wide range of both domain-specific and general libraries are available for statistics, machine learning and numerical modelling.
This online workshop will start by briefly covering the basics of Julia’s syntax and features, and then introduce methods and libraries which are useful for writing high-performance code for modern HPC systems. After attending the workshop, you will:
Introduction to Julia syntax and features.
Julia for data analysis, data frames, visualization, various data formats, read/write data, missing data.
Linear algebra, array matrix and vector operations, performance comparisons, random matrices, sparse matrices, eigenvalues/eigenvectors and PCA.
Clustering, classification, machine learning, deep learning.
Regression, time series analysis and prediction.
Registrations are now closed.
This training is intended for users established in the European Union or a country associated with Horizon 2020. You can read more about the countries associated with Horizon2020 here https://ec.europa.eu/info/research-and-innovation/statistics/framework-programme-facts-and-figures/horizon-2020-country-profiles_e