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EMOS/FEP Webinar 'A brief tour of Julia programming language'

Thursday, May, 13th - 6:30 pm online

By Sérgio Bacelar, Statistics Portugal

Julia language: “looks like Python, feels like Lisp, runs like C”.
In this webinar, Sergio will introduce Julia as one of the most promising tools in Data Science. He starts with the definition and origins and provides a little tour of 30 minutes approaching two language problems: performance versus simplicity - and also metaprogramming.

Join here.

These are the topics of the webinar: What is Julia, and where it is used. Language and applications perspective: JuliaLang and Julia Computing. How to learn Julia: documentation, community and tooling. Julia ecosystem and the data sciences subsystem: statistics, machine learning, economics, agent-based modelling. JuliaHub and Julia Observer. Popular and most relevant packages. Package manager. Package compatibility and project environments. Comparison with other programming languages: syntax (using Unicode, no curly braces or white space, type annotations, abstract numbers, everything is an expression), benchmarks and design. Reasons for efficiency. Rules to create efficient code. Nuts and bolts of Julia programming language. Data structures: tuples, named tuples, dictionaries and arrays. Functional programming: anonymous functions and closures, one-liner and multiline functions with type annotations. Types: concrete and abstract types, type hierarchy (supertypes and subtypes), composite types and type stability. Julia ‘secret sauce’: multiple dispatch as the core feature of Julia language design.

Short bio
Sérgio works at the Department of Demographic and Social Statistics of Statistics Portugal, where he is responsible for producing the Well-being index of Portugal. He has been working in Statistics Portugal since 1999, mainly on statistical metadata, regional statistics studies and official statistics dissemination. He is also a PhD student of Complexity Sciences (FCUL-University of Lisbon/ISCTE-University Institute of Lisbon) and has a degree in Economics from the University of Porto and in Sociology from University Institute of Lisbon. His main research interests are Computational Social Sciences (agent-based modelling) and Well-being/Quality of Life research. The main areas of applications are retirement pension systems, well-being and official statistics. He has published papers and presented communications on well-being, computational social sciences, statistical metadata and regional statistical studies. Sérgio has been teaching and researching in areas related to social sciences methods, statistics and organizational behaviour at the Faculty of Economics of the University of Porto and other university schools. He has been coding mainly in R, but he is trying to use Julia as his first language.
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