# Mathematical Python

*Mathematical Python* is an introduction to mathematical computing including:

- Jupyter notebooks, markdown and $\LaTeX$
- Basic Python programming: datatypes, variables, logic, loops and functions
- Scientific computing with NumPy, SciPy and Matplotlib
- Applications in calculus, linear algebra and differential equations

## Prerequisites

We assume the reader has completed undergraduate courses in:

- Differential calculus: derivatives, Taylor series and optimization
- Integral calculus: integrals, Riemann sums, sequences and series
- Linear algebra: vector and matrix operations, systems of equations, eigenvalues and eigenvectors
- Differential equations: first and second order equations, Euler's method and systems of equations

## Author

Patrick Walls is Associate Professor of Teaching in the Department of Mathematics at the University of British Columbia.

## Feedback

Comments and suggestions are always welcome! Please contact Patrick Walls, make a pull request to the GitHub repo or share your thoughts in the Google form.

## Acknowledgements

*Thank you ...*

- Pacific Institute for the Mathematical Science (PIMS) for creating Syzygy and hosting Jupyter notebooks for thousands of students and researchers across Canada
- Jupyter, Python and SciPy developers for creating open source scientific software
- MkDocs developers and Martin Donath for creating a Material Design theme for MkDocs

## License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

## Last Modified

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August 16 2022 14:12 PST
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