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Python for Engineers and Scientists

via LinkedIn Learning

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Find out how practicing scientists, engineers, and students of science and engineering can use Python to help make their work more efficient.

Syllabus

Introduction

Become a better engineer or scientist with Python
What you should know

1. Installation

macOS installation
Windows and Linux installation
Working with Jupyter notebooks
Using the exercise files

2. Make It Fast

Making Python code fast
Introduction to NumPy arrays
Matrix operations with NumPy
Linear algebra and sparse matrices with NumPy and SciPy
Code generation with Numba and Cython
Wrapping legacy code with Cython, CFFI, and F2PY
Challenge: Diffusion equation
Solution: Diffusion equation

3. Make It Right

Making Python code right
Symbolic computation with SymPy
Units, constants, timescales, and more with Astropy
Differential equations with SciPy
Interpolation and optimization with SciPy
Debugging with ipdb
Challenge: Planetary conjunctions
Solution: Planetary conjunctions

4. Make It Easy

Making Python code easy
Web resources with requests and JSON
Tables with pandas
Scientific datasets with HDF5
Automation with Python scripts
Scientific workflows with Snakemake
Challenge: Perfect numbers
Solution: Perfect numbers

Conclusion

Next steps

Taught by

Michele Vallisneri

Reviews

4.6 rating at LinkedIn Learning based on 360 ratings

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