Introduction

Preface

This web site provides an introduction to the new computer language of Julia, which has recently expanded to perform the functions of differential equations. This tutorial is made solely for the purpose of education, and intended for students taking APMA 0330 (Methods of Applied Mathematics - I) course at Brown University. The tutorial accompanies the textbook Applied Differential Equations. The Primary Course by Vladimir Dobrushkin.

Julia is a relatively new language design for high performance speeds while compiling effecient native code for multiple platforms via LLVM. It also has a high level syntax that makes it an accesible background for programmers of any background or any experience level

To learn more about the language, go to the "Julia Homepage" link found in the navigation bar

Using Julia on Jupyter Notebook

To download the latest version of Julia, go to the "Downloading Julia" link on the top navigation bar.

Julia can be use on multiple platforms. During my personal use, I found using Jupyter Notebook to be the most useful and user-friendly

A prerequist for Jupyter Notebook Python, to install Python (Python 3.3 or greater, or Python 2.7) click here. What also can be used it the miniconda distribution which includes a minimal Python and conda installation. Now, in the Anaconda Prompt, the following code can be used to install the notebook:

conda install -c conda-forge notebook

Now Jupyter Notebooks is installed. To run the notebook, run the following command in the Anaconda or Windows Prompt:

jupyter notebook

For questions Email: Prof. Vladimir Dobrushkin. Prof. Vladimir Dobrushkin.