Mathematical Python is an introduction to mathematical computing including:
- Jupyter notebooks, markdown and $\LaTeX$
- Basic Python programming: datatypes, logic, loops and functions
- Scientific computing with NumPy, SciPy and Matplotlib
- Applications in calculus, linear algebra and differential equations
Mathematical Python is a collection of Jupyter notebooks and are available at:
If you have a UBC CWL:
We assume the reader has completed undergraduate courses in:
- Differential calculus: derivatives of elementary functions, Taylor series and optimization
- Integral calculus: Riemann sums, sequences and series
- Linear algebra: vector and matrix operations, systems of equations, eigenvalues and eigenvectors
- Differential equations: Euler's method for first order equations, linear systems of ODEs
Patrick Walls is an instructor in the Department of Mathematics at the University of British Columbia and teaches mathematical computing, differential equations and vector calculus for mechanical engineering.
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 transformative open source tools.
- MkDocs developers and Martin Donath for creating a Material Design theme for MkDocs.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Wed 4 Dec 2019 17:20:04 PST