Computational Methods

Computational methods, astrostatistics, machine learning, visualization, and general coding.

Courses

Resources from the LSSTC Data Science Fellowship Program sessions
Resources from Code/Astro workshops
Introductory tutorials from Yale’s ASTR 255/PHYS 295: Research Methods in Astrophysics for undergraduate majors by Ava Polzin
Notebooks from Daniel Green’s Physics 105B: Computational Physics at University of California, San Deigo
Notebooks from Daniel Green’s Physics 39: Scientific Computing with Python at UCSD
Tutorials from Philip Mocz on Medium – note that these are “member only”, which limits how many can be accessed per month without an account
Python tutorials from Jackie Champagne
Lectures and tutorials from the 10-week KITP program Building a Physical Understanding of Galaxy Evolution with Data-Driven Astronomy led by Tjitske Starkenburg, Francisco Villaescusa-Navarro, Peter Behroozi, and John Wu (overall program here)
Scientific Computing Toolbox by Shane Burns (see also Linear Fitting)
MacOSX Unix Tutorials by Shane Burns
Notes from Stanford KIPAC’s graduate Physics 366: Statistical Methods in Astrophysics (also on GitHub)
Notes from Stanford KIPAC’s Physics 89L: Introduction to Data Analysis, with Python and Jupyter

Yale’s senior undergraduate ASTR 330: Scientific Computing in Astrophysics by Imad Pasha and Marla Geha
Stony Brook’s graduate PHY 504: Computational Methods in Physics & Astrophysics I by Michael Zingale
Stony Brook’s undergraduate AST 390: Computational Astrophysics by Michael Zingale
Lecture notes from Daniel Green’s Physics 105B: Computational Physics at the UCSD
Notes from UCSD’s Physics 39: Scientific Computing with Python by Daniel Green
Notebooks and materials from Viviana Acquaviva’s Machine Learning for Physics and Astronomy
Model Interpretability from the 2023 IAIFI Summer School by Alex Gagliano and Josh Speagle
Practical Guidance for Bayesian Inference in Astronomy – Eadie et al. (2023)
Statistics and Machine Learning for Astronomy lecture videos and course website for Australia National University’s ASTR 4004/8008: Astronomical computing by Yuan-Sen Ting
Direct download of Romain Teyssier’s course notes in Scientific Computing
Direct download of Romain Teyssier’s course notes for Computational Astrophysics for PhD students
Yale University’s Astro Research Preparation Series
Slides from University of Wisconsin-Madison’s undergraduate Machine Learning in Physics by Moritz Münchmeyer