This is a repository with material for the course Advanced Mathematics for Engineers. The program of the course is located here. A commented list of references can be found here.

• Notebooks: This folder contains several Jupyter Notebooks.

  • Sympy Tutorials:

    • SymPy in 10 minutes

    • Linear Algebra in SymPy

    • Ordinary differential equations in SymPy

    • Laplace Transform

  • Lessons:

    • Vector calculus and coordinate systems

    • Orthonormal basis and Fourier Analysis

• Slides

  • Course presentation

  • Linear transformations

  • Vector calculus and coordinate systems

  • Orthonormal basis and Fourier Analysis

You can clone the repo using:

git clone https://github.com/nicoguaro/AdvancedMath

or directly use the download option from GitHub.

To display the slides a browser is needed. They have been tested in Mozilla Firefox and Google Chrome, but any modern browser should work.

You can create an Anaconda environment using

conda env create -f environment.yml

This repository includes Jupyter Notebooks. To run these you will need Python and some packages:

• IPython, a command shell for interactive computing in multiple programming languages that offers introspection, rich media, shell syntax, tab completion, and history.

• NumPy, an extension to the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large library of high-level mathematical functions to operate on these arrays.

• SciPy, an open source Python library used for scientific computing and technical computing.

• matplotlib, a plotting library for the Python programming language and its numerical mathematics extension NumPy.

and the Computer Algebra System (CAS) Sympy. The suggested method is to download a Python Distribution, preferably Anaconda. This will include all the packages mentioned above.

For instruction on how to compile the source codes into the html files see the following section.

The slides for some lectures are in the folder Slides as .html files. They were written as Markdown (.md) files, and compiled with pandoc using

 pandoc -t slidy --css style.css -s slides.md -o slides.html

or

 pandoc -t slidy --css style.css --mathjax -s slides.md -o slides.html

to use MathJax to render the equations.

All code is under MIT license and media under Creative Commons Attribute.

The content of this reposirtory is licensed under the Creative Commons Attribution 4.0 license, and the source code that accompany the content is licensed under the MIT license.