Introduction to Julia Programming

Give developers the fundamental syntax, libraries, and tooling needed to write, debug, and profile Julia code for data science and scientific computing.

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Audience: Developers, architects

Duration: Three days

Format: Lectures and hands-on labs.

Overview

Julia is gaining popularity for scientific computing and ML due to its high performance and easy syntax. This course introduces Julia language and ecosystem.

Objective

Give developers the fundamental syntax, libraries, and tooling needed to write, debug, and profile Julia code for data science and scientific computing.

What You Will Learn

Julia vs other languages
REPL & development environment
Data types, variables, functions
Arrays, control flow, modules
DataFrames & visualisation
Metaprogramming, macros, performance profiling
Intro to ML with Julia

Course Details

Audience: Developers, architects

Duration: Three days

Format: Lectures and hands-on labs.

Prerequisites:

Programming experience with Python or Java

Setup: Laptop with Internet • Julia dev environment

Detailed Outline

Ecosystem, features, setup

Variables, types, scope

Loading & exploring data

Plots & packages

Statistics, missing values

Macros, code gen

Profiling, benchmarks

Linear regression