This repository contains all labs and projects for the course Physics C170M at UCLA taught by Professor Tuan Do in Winter Quarter 2024. All credit for labs, ipynbs, pdfs goes to Professor Do, Dr. Bernie Boscoe, and the Physics and Astronomy department at UCLA. The only orignally generated work is our final project for the course. People work together in groups of 4 and the topic differs from group to group. For more details, refer to the Final_Project folder. Our topic was "Inferring Cosmological Parameters from Void Properties Using Fully Connected Neural Networks." It is based off this paper written by Dr. Bonny Y. Wang, Dr. Alice Pisani, Dr. Francisco Villaescusa-Navarro, and Dr. Benjamin D. Wandelt. In particular, Dr. Wang, Dr. Pisan, and Dr. Villaescusa-Navarro provided us invaluable guidance in navigating their work and understanding the intricacies of their neural networks.