Skip to content

jbduarte/SGPE_Numerical_Course

Repository files navigation

SGPE Numerical Course

Binder

This course is designed for students interested in learning how to apply numerical methods in Python in order to solve quantitative problems in statistics, finance and economics. This course aims at equipping students with computational tools available in Python and on its main packages: Numpy, Pandas and Matplotlib. The learning process will be based on hands-on activities. The general approach will be to give a brief theoretical description of the methods followed by examples, whereby students will apply themselves the methods in Python. The course will run for 5 days with 3 hours classes in the morning, and 3 hours classes in the afternoon.

Useful Cheat Sheets of Matlab vs. Python vs. Julia Link

https://cheatsheets.quantecon.org/index.html

Speeding Up Python with Numba Intro Link

https://notes.quantecon.org/submission/5b2d5ea1b9eab00015b89f76

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages