Intermediate Julia

Overview

Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.

Julia is a relatively new programming language built with speed and performance in mind, and it can do this while maintaining a similar syntax to other programming languages such as Python or Ruby. This course follows the Introduction to Julia course, introducing topics such as looping and timing so that you can take advantage of Julia's speed and performance.

Build on Your Julia Foundations

Building on the core concepts of the introductory course, you will be one step closer to mastering Julia. You will first learn about different loops, one of the most common tools in Julia, and all programming languages.

Cover Advanced Julia Data Structures

You'll also cover advanced data structures, including dictionaries, tuples, and structs. In addition, you will learn how to define your own Julia functions for code re-usability and how to time your code to be as efficient as possible.

At the end of this course, you'll be able to work with more complex DataFrame operations to inspect and clean a global video game sales dataset broken down by region. You will also be able to leverage your Python and R knowledge in Julia as we introduce the PyCall and RCall packages, allowing you to use Python and R functions in Julia.

By the time you finish, you'll have built a strong Julia programming foundation which you can continue to develop through further courses.

Syllabus

Loops and Ranges

Loops are one of the core concepts that underpin Julia. In this chapter, you'll learn about for loops and while loops, and how to use them to iterate over data structures that you are already familiar with. You will also cover ranges, a useful tool for generating sequences of data.

Data Structures

This chapter focuses on expanding your knowledge of the data structures available in Julia. Learn how to use tuples, dictionaries, multi-dimensional arrays, and structures to store and traverse data quickly and efficiently.

Advanced Functions in Julia

In this chapter, you’ll extend your understanding of functions, exploring positional, keyword, and default function arguments. You will also cover code execution timing, getting a strong understanding of how to measure the time your code takes to run. This chapter will round off with a capstone on writing your own functions to solve real-world problems.

Dataframe Operations and Python/R Packages in Julia

This final chapter will introduce anonymous functions and will recap one of the powerful features of Julia; multiple dispatch. You will learn how to use functions from Python and R packages within Julia and discover how to clean and modify data within dataframes.