STAT 121b/ CS 109b: Data Science

Spring 2017 & 2018 - Harvard University

"Building upon the material in Data Science 1, the course introduces advanced methods for data wrangling, data visualization, and statistical modeling and prediction. Topics include big data and database management, interactive visualizations, nonlinear statistical models, and deep learning."

Lab Leader 2018

STAT 139: Statistical Sleuthing Through Linear Models

Fall 2016 - Harvard University

"A serious introduction to statistical inference with linear models and related methods. Topics include t-tools and nonparametric alternatives (including bootstrapping and permutation-based methods), multiple-group comparisons, analysis of variance, linear regression, model checking and refinement, and causation versus correlation. Emphasis on thinking statistically, evaluating assumptions, and developing tools for real-life applications."

Academic Development Peer Tutor

Spring 2012 : Spring 2015 - Carnegie Mellon University

Topics Covered:

Advanced Data Analysis; Principles of Computing; Intro. to Statistics; Intro. Physics 1 & 2