Lecture Notes on Computational Cosmology (Graduate)
I taught an introduction to Computational Cosmology, my research domain, in Fall 2023. Computational Cosmology is the science of extracting physics from observational data in cosmology. It involves a mixture of theory, statistics and programming. If you are a student interested in doing research with me, these are the basics you should know (or learn) about. The level of these lecture notes should be suitable for beginning graduate students or advanced undergraduates.
I sometimes update these lecture notes so make sure you download the most recent version:
If you are an instructor using my notes, or find any mistakes, I’d be happy if you drop me an email. I’m also thankful to Utkarsh Giri and Sai Tadepalli for contributing material to these lectures.
We also did some computational examples and problems which I hope to publish here in the future.
Slides on Machine Learning in Physics (Undergraduate)
In Spring 2024 I taught a new course on Machine Learning in Physics for undergraduates (co-taught with Gary Shiu). AI in Physics is the second main topic of my research and I tried to convey some of the excitement in the field.
The slides for the class can be found here: Physics 361 – Machine Learning in Physics
I hope to update the course material over the years to keep up with this quickly evolving field.