Julia 1: Getting Started
Julia is a programming language designed for high performance that's used for Data Science, scientific domains, data visualization, parallel computing, and more. This course will teach you what you need to know to get started programming with Julia!
What you'll learn
Every language has pros and cons... but what if I tell you that there is a language that was created with the experience of many other programming languages, with performance in mind, and that is able to provide all kinds of features available in general programming languages all the way to languages designed for scientific computing and Data Science?
Well, that's what Julia is all about.
In this course, Julia 1: Getting Started, you'll learn foundational knowledge required to be a Julia programmer. First, you'll learn how to set up your Julia development environment. Next, you'll discover how to define variables and use data types as well as control program flow. That will be followed by learning how to create functions, methods, and modules, as well as how to work with files. Finally, you'll see how to find packages that will help you build any application you can dream of.
When you're finished with this course, you'll have the skills and knowledge required to call yourself a Julia coder. Software required: Julia.
Table of contents
- Setting up Your Julia Development Environment 3m
- Installing Julia in Windows 10 2m
- Installing Julia in macOS 1m
- Installing Julia in Linux 2m
- Running Julia Code and the Web-based Shell Demo 3m
- Running Julia Code with the Interpreter Demo 2m
- Running Julia Code in an IDE Demo 3m
- Running Julia Code in Jupyter Notebook Demo 1m
- Takeaway 2m
- Learning How to Define Functions 9m
- Understanding the Difference between Functions and Methods 2m
- Deciding Which Method to Execute: Dispatch 1m
- Dealing with Ambiguity on Methods 1m
- Using Function Composition, Piping, and Dot Syntax 3m
- Grouping and Organizing Functionality with Modules 2m
- Takeaway 1m
Course FAQ
Some benefits of the Julia programming language are: Julia is fast, contains a math-friendly syntax, automatic memory management, and offers superior parallelism.
Some basics principles to programming are: data types, variables, keywords, loops, numbers, characters, and arrays, inputs, outputs, conditions, and ins and outs to name a few.
Prerequisites for this course are: an understanding of programming in general, preferred knowledge of Python, R, or Scala, and as a bonues, a mathematical background.
Parallel computing is a type of computation where many calculations or the execution of processes are carried out simultaneously.
About the author
Xavier Morera is driven by one passion: taking on the challenge of understanding complex topics and sharing that knowledge with others. He’s currently focused on the transformative fields of AI, machine learning, generative AI, search, and big data. As an entrepreneur, project manager, technical author, and trainer, Xavier brings a diverse set of skills and deep expertise to every project he takes on. He holds multiple certifications with Cloudera, Microsoft, and the Scrum Alliance and has been... more