- Julia Tutorial
- Julia - Home
- Julia - Overview
- Julia - Environment Setup
- Julia - Basic Syntax
- Julia - Arrays
- Julia - Tuples
- Integers & Floating-Point Numbers
- Julia - Rational & Complex Numbers
- Julia - Basic Operators
- Basic Mathematical Functions
- Julia - Strings
- Julia - Functions
- Julia - Flow Control
- Julia - Dictionaries & Sets
- Julia - Date & Time
- Julia - Files I/O
- Julia - Metaprogramming
- Julia - Plotting
- Julia - Data Frames
- Working with Datasets
- Julia - Modules and Packages
- Working with Graphics
- Julia - Networking
- Julia - Databases
- Julia Useful Resources
- Julia - Quick Guide
- Julia - Useful Resources
- Julia - Discussion
Julia Tutorial
One of the facts about scientific programming is that it requires high performance flexible dynamic programming language. Unfortunately, to a great extent, the domain experts have moved to slower dynamic programming languages. There can be many good reasons for using such dynamic programming languages and, in fact, their use cannot be diminished as well. On the flip side, what can we expect from modern language design and compiler techniques? Some of the expectations are as follows −
It should eradicate the performance trade-off.
It should provide the domain experts a single environment that is productive enough for prototyping and efficient for deploying performance-intensive applications.
Audience
This tutorial will be useful for graduates, post-graduates, and research students who either have an interest in Julia Programming or have these subjects as a part of their curriculum. The reader can be a beginner or an advanced learner.
Prerequisites
The reader should have knowledge on basic computer programming languages.