Courses

CS234

• Solid introduction to the field of reinforcement learning
• Covered topics such as Tabular MDP planning, Tabular RL policy evaluation, Q-learning, RL with function approximation, Policy search, Fast Learning, and Batch Reinforcement Learning
• Developed my own RL agents with PyTorch and OpenAI gym

CS144

• Computer networking principles and protocols
• Used C++ to create reliable data transport mechanisms
• Implemented core functionalities of TCP/UDP from scratch, gaining understanding of internet architecture and data flow
• Routing and congestion theory

CS107E

• Bare metal C programming in a Raspberry Pi
• Developed my own kernel modules from scratch, including memory allocation, keyboard and mouse drivers, graphics library and cpu-gpu message handling

Chinese

• My objective is to reach intermediate fluency until I graduate, so I plan to take it every quarter

AI Alignment

• Understand existing AI safety technical research
• Discuss efforts to implement policy measures that reduce AI risk
• Good overall perspective into the field of AI and its most cutting-edge advancements

Math 61DM

• Rigourous, proof-based Linear Algebra through a innovative Discrete approach with combinatorics

CS109

• Probability for Computer Scientists
• Formal Probability, Bayesian Networks, and basic Machine Learning

CS231n

• Computer Vision and Deep Learning
• Developed new road segmenation model

CS111

• Operating Systems

CS137a

• All-emcompassing introduction to autonomous robotics