Python for Engineers and Scientists
Offered By: LinkedIn Learning
Course Description
Overview
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
- macOS installation
- Windows and Linux installation
- Working with Jupyter notebooks
- Using the exercise files
- 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
- 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
- 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
- Next steps
Taught by
Michele Vallisneri
Related Courses
Scientific ComputingUniversity of Washington via Coursera Biology Meets Programming: Bioinformatics for Beginners
University of California, San Diego via Coursera High Performance Scientific Computing
University of Washington via Coursera Practical Numerical Methods with Python
George Washington University via Independent Julia Scientific Programming
University of Cape Town via Coursera