Teaching

In the upcoming year, I am teaching the following courses:

DSCI 511 - Programming for Data Science

Program design and data manipulation with Python.

DSCI 571 - Supervised Learning I

Basic concepts in supervised learning such as overfitting, generalization gap, optimization bias. Intro to models including decisions trees, KNN classifiers, and logistic regression.

DSCI 572 - Supervised Learning II

Introduction to numerical optimization (e.g., gradient descent). Neural networks and deep learning.

DSCI 563 - Unsupervised Learning

How to find groups and other structure in unlabeled, possibly high dimensional data. Dimension reduction for visualization and data analysis. Clustering, association rules, model fitting.