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Intermediate Julia

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

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4 Hours15 Videos54 Exercises

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Course Description

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.
  1. 1

    Loops and Ranges

    Free

    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.

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    For loops
    50 xp
    For loops question
    50 xp
    Loop over a vector
    100 xp
    Loops and enumerate
    100 xp
    Looping over nested structures
    100 xp
    While loops
    50 xp
    Writing a while loop
    100 xp
    While loops for iteration
    100 xp
    Ranges
    50 xp
    Ranges - iteration
    50 xp
    Defining ranges
    100 xp
    Looping over ranges
    100 xp
    Splat unpacking
    100 xp
  2. 3

    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.

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  3. 4

    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.

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In the following tracks

Julia Fundamentals

Collaborators

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Izzy Weber
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Arne Warnke
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Maham Khan
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Katerina Zahradova
Anthony Markham HeadshotAnthony Markham

Quantitative Developer

Anthony is a Quant Developer in Algorithmic Trading and Risk Management in Sydney, Australia. With a background in Aerospace and Software Engineering, Anthony has experience in Data Science, facial recognition research, tertiary education, and Quantitative Finance, developing mostly in Python, Julia, and C++. When not working, Anthony enjoys working on personal projects, flying aircraft, and playing sport.
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