UC Berkeley Coursework

Spring 2024

Did not take any technical courses this semester. Focused purely on research.

Fall 2023

CS 162: Operating Systems and System Programming - Natacha Crooks
CS 170: Efficient Algorithms and Intractable Problems - John Wright, Nika Haghtalab
CS 370: Adaptive Instruction Methods in Computer Science - Christopher Hunn

Summer 2023

CS 160: User Interface Design and Development - Michael Ball

Spring 2023

CS 189: Introduction to Machine Learning - Jonathan Shewchuk
EECS 127: Optimization Models in Engineering - Gireeja Ranade
CS 161: Computer Security - Raluca Ada Popa, Peyrin Kao

Fall 2022

CS 186: Introduction to Database Systems - Alvin Cheung
Data 140: Probability for Data Science - Ani Adhikari
CS 194-224: Entrepreneurship in Web3 - Xiaodong Dawn Song
EECS 16B: Designing Information Devices and Systems II - Sayeef Salahuddin, Yi Ma
Stat 33B: Introduction to Advanced Programming in R - Gaston Sanchez Trujillo

Summer 2022

CS 61C: Great Ideas in Computer Architecture (Machine Structures) - Caroline Xinwei Liu, Justin Yokota
CS 70: Discrete Mathematics and Probability Theory - Jingjia Chen, Tarang Srivastava, Michael Peter Psenka

Spring 2022

CS 61B: Data Structures - Paul N Hilfinger
Data C100: Principles and Techniques of Data Science - Joshua A Hug, Lisa Yan
EECS 16A: Designing Information Devices and Systems I - Ana Claudia Arias, Miki Lustig
Econ 100A: Microeconomics - James D Campbell

Fall 2021

CS 61A: Structure and Interpretation of Computer Programs - John Denero, Pamela Fox
Stat 88: Probability and Mathematical Statistics in Data Science - Anthony Cyril Donoghue
UGBA 10: Principles of Business - Daniel Mulhern, John Briginshaw, Jonathan Heyne, Judy Hopelain, Omar Romero-Hernandez, Torsor Kotee
Math 1B: Calculus - Alexander Paulin

Summer 2021

Data C8: Foundations of Data Science - Ani Adhikari

Self-Study Courses

UC Berkeley CS 285: Deep Reinforcement Learning - Sergey Levine
MIT 18.06: Linear Algebra - Gilbert Strang