Short course: AI for Statistical Analysis

Dr. Reetam Majumder from the University of Arkansas will lead a three-hour short course on AI for statistical analysis from 2:00 to 5:00 pm on Friday, October 31, 2025, in room 104 of UMBC's Math & Psychology building. The course will provide a hands-on introduction to deep learning models using the Keras package in R.

Register here by October 24.

Deep learning is the cornerstone of all current AI models. While they have historically been used extensively in supervised and unsupervised learning problems, deep learning is also seeing increased adoption for statistical inference associated with complex/intractable models, massive datasets, or both. The short course will provide a hands-on introduction to deep learning models using the keras package in R.

The course aims to familiarize statisticians with the entire pipeline for analyzing data, including software setup, data preprocessing, and some common neural network architectures used in predictive modeling for different data types like tables, images, and time series. Participants will also be introduced to deep learning approaches for density estimation and parameter estimation in statistical problems, and an overview of the current state-of-the-science. 

The hands-on sections will be demonstrated on Google Colab, and participants will be able to follow along on their own personal devices. Course materials, including code, data, slides, and resources for installing the Keras and Torch deep learning libraries on R, will be made available on GitHub.