Coursework
These list consists of my coursework taken at UC Berkeley, MIT, and USC.
Graduate Level Coursework
Computer Science
- 6.5940 (TinyML and Efficient Deep Learning Computing)
- 6.7920 (Reinforcement Learning: Foundations and Methods)
- 6.8200 (Sensorimotor Learning)
- 6.8300 (Advances in Computer Vision)
- 15.095 (Machine Learning via a Modern Optimization Lens)
- 15.622 (Law of AI)
- 17.835 (Machine Learning in Politics)
- CSCI 699-30165 (Probabilistic and Generative Models )
- CSCI 699-30132 (Trustworthy Large Foundation Models )
Operation Research
- 6.7830 (Bayesian Modeling and Inference)
- 6.C57 (Optimization)
- 6.7220 (Nonlinear Optimization)
- 15.072 (Advanced Analytics Edge)
- 15.572 (Analytics Lab, Machine Learning, Digital Economy)
- 15.094 (Robust Modeling, Optimization & Computation)
- 15.873 (System Dynamics)
Mathematics
Electrical Engineering
Undergraduate Level Coursework
Computer Science
- CS 61A (The Structure and Interpretation of Computer Programs)
- CS 61B (Data Structures)
- CS 61C (Great Ideas of Computer Architecture)
- CS 70 (Discrete Mathematics and Probability Theory)
- CS 170 (Efficient Algorithms and Intractable Problems)
- CS 188 (Introduction to Artificial Intelligence)
- CS 282A (Deep Neural Networks )
- CS 289A (Machine Learning )
- INFO 259 (Natural Language Processing )
Mathematics
- Math 53 (Multivariable Calculus)
- Math 54 (Linear Algebra and Differential Equations)
- Math 55 (Discrete Math)
- Math 104 (Introduction to Analysis)
- Math 110 (Linear Algebra)
- Math 113 (Introduction to Abstract Algebra)
- Math 115 (Introduction to Number Theory)
- Math 124 (Programming for Mathematical Applications)
- Math 130 (Classical Geometries)
- Math 185 (Complex Analysis)
- Math 191 (Putnam Workshop)
- MAT 215 (Single Variable Analysis with an Introduction to Proofs)
Statistics
- Data 8 (The Foundations of Data Science)
- Stat 33B (Introduction to Advanced Programming in R)
- Data 100 (Principles and Techniques of Data Science)
- Stat 134 (Concepts of Probability)
- Stat 135 (Concepts of Statistics)
- Stat 150 (Stochastic Processes)
- Stat 151A (Linear Modelling, Theory and Applications)
- Stat 155 (Game Theory)
- Data H195 (Senior Honors Thesis)
Electrical Engineering
- Engin 7 (Computer Programming for Scientists and Engineers)
- EE 16A (Designing Information Devices and Systems I)
- EE 16B (Designing Information Devices and Systems II)
- EE 120 (Signals and Systems)
- EE 126 (Probability and Random Processes)
- EE 227A (Optimization Models in Engineering )
- EE 482 (Linear Control Systems)
:)