by Jeff Bezanson (@jeff0) on Tuesday, September 15, 2015

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Status: Confirmed & Scheduled
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Section
Workshop

Technical level
Beginner

Objective

Participants of this workshop will learn about the features of the Julia language, its package ecosystem and how to build scalable real-time data-intensive applications in a series of hands-on learning sessions.

Description

Julia is a high-level, high-performance dynamic language, it uses just-in-time compilation to provide fast machine code - dynamic code runs close to the speed of C, and orders of magnitude faster than traditional numerical computing tools.

This workshop will be divided into 4 parts:

1. Analytics and data science with Julia We will demonstrate an end-to-end example of a data analysis workflow, from downloading publicly available data to loading data into Julia, creating summaries and answering business questions using visualization. You will also learn how to create interactive UIs to play with ideas at the speed of thought and eventually deploy user-facing applications entirely in Julia without writing any JavaScript.

2. Julia language constructs A complete overview of the Julia language, which includes concepts such as functions, standard library, types, multiple-dispatch, macros, introspection, modules, packaging and a brief look at the language infrastructure.

3. Working with big data and parallel computing What would you do with a thousand processors? In this session we will explore the parallel computing capabilities of Julia, integration with Hadoop file system tools for setting up data processing pipelines.

4. Pair-programming: build your own Julia application In this session you will pair up with a teammate to build a simple application (e.g. a recommendation engine) and deploy it as an auto-scaling REST applcation on JuliaBox or locally.

Requirements

  1. Install Julia 0.3 (you can also install 0.4-rc4 alongside, but 0.3 is required for the tutorial) see http://julialang.org/downloads

  2. Install the following packages by running Pkg.install(“<package-name>”) in the Julia REPL.
    IJulia, Gadfly, PyPlot, Interact, JuMP, DataFrames - do not worry if you are having trouble installing any of these packages. We will have a server with all these installed as fallback but we want you to be prepared for a no-internet scenario.

It is recommended that if you use Windows, you install the Juno IDE

Speaker bio

This workshop will be conducted by the core developers of Julia most notably Jeff Bezanson, Stefan Karpinski and Viral B Shah