Teaching

STAT 213 - Introduction to Statistics I

Introduction to probability, including Bayes' law, expectations and distributions. Discrete and continuous random variables, including properties of the normal curve. Collection and visual display of single and multi-dimensional data. Introduction to statistical modeling and estimation. Parametric and simulation-based confidence interval estimation.

DATA 602 - Statistical Data Analysis -

An introduction to the foundations of statistical inference including probability models for data analysis, classical and simulation-based statistical inference, and implementation of statistical models with R.

DATA 603 - Statistical Modelling with Data

An introduction to the creation of complex statistical models, including exposure to multivariate model selection, prediction, the statistical design of experiments and analysis of data in R.

DATA 607 - Statistical and Machine Learning

Inrtodcuiton of basic techiques of statistical and machine learning models including data transformation methods, classification, model assessment and selection. Exposure to both supervised learning and unsupervised learning. Most materials are from the classic book "An Introdcution to Statistical Learning" with a bit of modern deep learning mehtods covered.

STAT 601.28 - Topics in Probability and Statistics (Deep Learning and Its Hands-on Practice)

An overview of deep learning models, focusing on hands-on practice of model implementation and data anaysis using state-of-the-art libraries.