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Discover how to declare and use variables in Julia, including numbers, strings, and unicode-based identifiers via backslash input, and learn about the ANS variable and other naming conventions.
Explore arrays in Julia, using 1-based indexing to access and modify elements, build 1d and 2d arrays, perform element-wise addition and multiplication, and select rows or columns with colon notation.
Explore how Julia functions work: define with the function keyword or shorthand, pass parameters, return values, and treat functions as values, using examples like sqrt(25) and sort.
Explore returning values from functions with the return keyword, including conditional returns in a daily interest calculator; use anonymous functions, map, and keyword arguments with defaults in Julia.
Define functions with a variable number of arguments using ellipses and explore function signatures; apply map to square inputs; build a planet weight calculator and a credit card interest calculator.
Discover Julia's dynamic type system using typeof to inspect values and trace subtypes through the hierarchy. Declare custom types with the type keyword; define a person with ASCII string fields.
Explore how loops work in Julia by iterating through arrays and dictionaries with for loops, and control flow with while loops and conditional logic.
Explore list comprehensions in Julia by transforming and filtering arrays with for-like syntax, including squaring numbers, applying conditions, and using filters for even elements, paralleling map usage.
Explore Julia metaprogramming by examining expressions and symbols, parsing strings into expressions, and constructing symbol-based computations to understand how Julia compiles and executes code.
Learn how to use constants and typing to improve Julia performance, especially for global variables. Explore time macro timing and the impact of initial compilation versus subsequent runs.
Demonstrate exception handling and robust error management in Julia by using try-catch, domain errors, and custom messages, while validating user input and logging failures to prevent crashes.
Explore advanced exception handling in Julia by using inline try catch blocks, handling errors and warnings, and applying finally to ensure files are closed and cleanup after failures.
The secret to making the big bucks and landing that dream programming job is pretty simple. Pick a few key languages and get really, really good at them. Choosing languages that have a solid foundation and a promising future is also a good idea; and Julia fits that bit perfectly. This relatively new kid on the block (its first release was in 2012) is on the verge of becoming huge, and this online course will help you get one step ahead of everyone else by learning it fast, and learning it now.
Get Ahead of the Coding Curve
Learn Julia Fundamentals
This Julia online course will take you from complete beginner to intermediate. Starting at the very beginning, you will be guided through the installation process and the basic functions and features of Julia will be presented to you. Variables, strings, logical operators, arrays, types, dictionaries, loops, list comprehensions, scope and modules are all covered to give you a thorough footing in the world of Julia.
The second half of the course moves into more advanced features. You’ll dive into File IO reading, directories and learn how to write to files before moving on to meta programming, error handling, and various other more complex features of Julia. Each lesson provides download-able code so you don’t miss a trick and can go back over the material at your leisure.
Anyone who has a handle on basic programming concepts will get through this course with flying colours, as will those who are completely new to Julia and programming in general. You don’t need any previous credentials to begin... in fact, all you need is a computer with an internet connection to be on your way to a glittering programming career.
About Julia
Julia is a high-level, high-performance, dynamic programming language mostly used for technical, numerical and statistical computing. It’s also becoming increasingly popular for general-purpose programming, web use and as a specification language. It combines the powerful performance of C with the prototyping of Python.