Academics

University of California, Berkeley (2016-2020)

Stat 153: Time Series (Fall 2019, J. Fisher)
Stat 102: Data, Inference, and Decisions (Fall 2019, M. Jordan and F. Perez)
Stat 154: Modern Statistical Prediction and Machine Learning (Spring 2019, B. Yu)
Stat 152: Sampling Surveys (Spring 2019, E. Purdom)
Stat 150: Stochastic Processes (Fall 2018, B. Kolesnik)
Stat 151A: Linear Modelling (Fall 2018, O. Padilla)
Stat C100: Principles & Techniques of Data Science (Fall 2018, J. Hug and F. Perez)
Stat 135: Concepts of Statistics (Spring 2018, H. Ibser)
Stat 133: Concepts in Computing with Data (Spring 2018, G. Sanchez)
Stat 134: Concepts of Probability (Fall 2017, H. Ibser)
Stat C8: Foundations of Data Science (Spring 2018, A. Adhikari)

Math 185: Complex Analysis (Fall 2019, N. Miller)
Math 170: Mathematical Methods for Optimization (Spring 2019, L. Evans)
Math 128A: Numerical Analysis (Fall 2018, J. Wilkening)
Math 202A: Topology and Analysis* (Fall 2018, M. Rieffel)
Math 113: Abstract Algebra (Summer 2018, A. Paulin)
Math 104: Real Analysis (Spring 2018, M. Pejic)
Math 110: Linear Algebra (Fall 2017, Z. Stankova)
Math 55: Discrete Mathematics (Summer 2017, Z. Jiang)
Math 54: Linear Algebra and Differential Equations (Spring 2017, K. Wehrheim)
Math 53: Multivariable Calculus (Spring 2017, E. Frenkel)
Math 1A: Calculus (Fall 2016, A. Paulin)

CS 182: Designing, Visualizing and Understanding Deep Neural Networks (Spring 2020, F. Canny)
Info 159: Natural Language Processing (Spring 2020, D. Bamman)
CS 375: Teaching Techniques for Computer Science (Fall 2019, M. Ball)
CS 188: Artificial Intelligence (Summer 2018, A. Baroudi and D. Fried)
CS 61A: Structure and Interpretation of Computer Programs (Fall 2016, J. De Nero)

*Course audited