The Julia programming language is acclaimed in scientific circles for its unparalleled ease, interactivity, and speed. Practical Julia is a comprehensive introduction to the language, making it accessible even if you’re new to programming. Dive in with a thorough guide to Julia’s syntax, data types, and best practices, then transition to craft solutions for challenges in physics, statistics, biology, mathematics, scientific machine learning, and more. Whether you’re solving computational problems, visualizing data, writing simulations, developing specialized tools, Practical Julia will show you how. As you work through the book, you’ll: • Use comprehensions and generators, higher-level functions, array initialization and manipulation, and perform operations on Unicode text • Create new syntax and generate code with metaprogramming and macros, and control the error system to manipulate program ution • Visualize everything from mathematical constructs and experimental designs to algorithm flowcharts • Elevate performance using Julia’s unique type system with multiple dispatch • Delve into scientific packages tailored for diverse fields like fluid dynamics, agent-based modeling, and image processing Whether your interest is in scientific research, statistics, mathematics, just the fun of programming with Julia, Practical Julia will have you writing high-performance code that can do real work in no time. Online Resources: Ready-to-run code samples, illustrations, and supplemental animations available at https://julia.lee-phillips.org.

Introduction PART I: LEARNING JULIA Chapter 1: Getting Started Chapter 2: Language Basics Chapter 3: Modules and Packages Chapter 4: The Plotting System Chapter 5: Collections Chapter 6: Functions, Metaprogramming, and Errors Chapter 7: Diagrams and Animations Chapter 8: The Type System PART II: APPLICATIONS Chapter 9: Physics Chapter 10: Statistics Chapter 11: Biology Chapter 12: Mathematics Chapter 13: Scientific Machine Learning Chapter 14: Signal and Image Processing Chapter 15: Parallel Processing Index