Julia is a high-level dynamic programming language designed to address the requirements of high-performance numerical and scientific computing. It has been discussed as one of the languages that could be the future of high performance data analytics because of its performance capabilities with benchmarks comparable to C.
If you are looking to develop high performance data analytical solutions & considering Julia, here are a collection of tutorials to get you started.
This tutorial introduces the Julia language for data science tasks. It teaches some basics of image processing and uses a popular machine learning algorithm to identify the character from pictures. IJulia or Julia Studio may help you to write and run Julia code.
Learn X in Y minutes is a Whirlwind tours of (several, hopefully many someday) popular and ought-to-be-more-popular programming languages, presented as valid, commented code and explained as they go. Leah Hanson and Pranit Bauva are the major contributors of this tutorial.
Learn Julia the Hard Way is a work in progress, and will see times of intense development punctuated by times of not much happening. This is to the fact that the language is constantly changing and there is occasionally a need to go back and revisit older parts.
Samuel Colvin explained Julia as a series of examples of common operations in Julia. They assume you already have Julia installed and working (the examples are currently tested with Julia v0.3.7). This site is a non official series of examples of Julia.
This website presents a series of lectures on quantitative economic modelling, designed and written by Thomas J. Sargent and John Stachurski in Julia programming. These lectures have benefited greatly from comments and suggestions from various sources.
Material for a 2-day workshop on Julia by David P.Sanders. The material consists of directed exercises, aimed to provide a “hands-on” way of learning Julia by getting the user to try out ideas semi-autonomously, as opposed to standard tutorials, which tend to give all the answers immediately. For youtube link click.
This tutorial is divided into Beginner, Intermediate, and Advanced section. In beginner section the tutorials will help you to familiarize yourself with the Julia Studio environment and the basics of the language. In Intermediate section, the tutorial focuses on some of the language features that make Julia awesome, such as its type system and its vast library of statistical and numerical methods. The last Advanced section, help you refine your abilities with more challenging problems, that will help you to develop a mastery of the language.
Julia wikibook is less of a tutorial, and more a collection of notes and examples to help you while you’re learning Julia.
Randy Zwitch shares his observations that might be helpful for others looking to get started with Julia. His observations include text file importing, looping and vectorization.
MIT Open Courseware and MIT-X graciously provided support for recording of lectures, so that the wider Julia community can benefit from recording sessions. The material provided in the videos can be downloaded here.
This tutorial introduces beginners to Julia programming by simplified exposition of the language.
A tutorial series for Economists learning to program in the Julia language. The tutorial was addressed by Bradley J. Setzler, a PhD student in economics at The University of Chicago.
This is an official documentation on Julia Programming, which itself is a comprehensive guide which provides overview on all the aspects of Julia Programming.
If you are looking for Julia language support from experienced users, please visit juilabloggers.com.
Largol collected these tutorials list for Julia programming language.