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DataCamp

Intermediate Julia

via DataCamp

Overview

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

Building on the core concepts of Introduction to Julia, this course will get you closer to becoming a Julia master. You will learn about different loops and advanced data structures, including dictionaries, tuples, or structs. 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, working with more complex DataFrame operations to inspect and clean a dataset will be a breeze. You'll also be able to leverage your Python and R knowledge in Julia through the PyCall and RCall packages.

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.

Taught by

Anthony Markham

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