Courses taken at UC Berkeley

(Cumulative GPA: 3.97)

• STAT 215A: Statistical Models I (Stat. PhD core)

• CS281/STAT241A Statistical Learning Theory

• INDENG 262A: Mathematical Programming I (IEOR PhD core)

• STAT 201A: Introduction to Probability at an Advanced Level

• STAT 201B: Introduction to Statistics at an Advanced Level

• STAT 248: Analysis of Time Series

• STAT 230: Linear Models

• STAT 222: Masters of Statistics Capstone Project

• CS 282A: Designing, Visualizing and Understanding Deep Neural Networks (audited)

• STAT 210A: Theoretical Statistics (Stat. PhD core)

• STAT 256: Causal Inference

• CS 294 214: Efficient Algorithms and Computational Intractability in Statistics

• ELENG 229A: Information Theory and Coding (audited)