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index.qmd
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# Why? {.unnumbered}
The Julia Programming Language is revolutionizing technical and scientific computing across many industries.
Modern language features such as differentiability and multiple dispatch have made Julia the perfect tool for building
[SciML](sciml.ai) - an open source ecosystem for scientific machine learning libraries.
Amoung many other modules, the SciML ecosystem includes an acausal modeling framework and the most comprehensive
collection of differential equation solvers that exists today. These modules form the fundation of SciML and their
flexibility makes them viable tools for working in any industry. These tools are so powerful that they
open the door to advanced modeling and simulation capabilities in any domain. This project serves as a guide to
perform modeling and simulation to solve real problems with Julia and SciML.
This guide is a collection of notes, teachings and exercises from many sources including the exceptional books
_Principle of Object-Oriented Modeling and Simulation with Modelica 3.3_[^pooms] by Dr. Peter Fritzson and
_Modelica by Example_[^mbe] by Dr. Michael M. Tiller. All content is translated to Julia and uses various modules
from SciMl. Thank you everyone that contributed to these works.
This is a book created from markdown and executable code.
See @knuth84 for additional discussion of literate programming.
[^pooms]: Fritzson covers the Modelica language in impressive depth from the basic concepts such as cyber-physical,
equation-base, object-oriented, system, model, and simulation, while also incorporating over a hundred
exercises and their solutions for a tutorial, easy-to-read experience. Find a copy at
<https://ieeexplore.ieee.org/book/7022515>.
[^mbe]: Tiller takes a different and welcome approach by covering the Modelica language with practical examples
and by optimizing the book for online consumption. The book is available for free at
<https://mbe.modelica.university/> and provides a rich and interactive learning environment.