An introduction to the theory and applications of time series modeling with an emphasis on modeling and forecasting using the software. Topics include stationarity and autocorrelation, autoregressive, moving average, ARMA and ARIMA; forecasting and estimation; spectral analysis. Computational implementation in R. Basic programming skills is preferred. Prerequisite: DATA 3441, MATH 4313.

Exploration of large collections of computer-readable text ('corpora') and their application in research and industry. Topics center on natural language processing tools and techniques with a focus on major modern datasets up to web-scale. Prerequisite: FREN 3320, GERM 3310, GERM 4334, RUSS 3310, RUSS 4334, SPAN 3310, ARAB 3310, CHIN 3310, KORE 3310, or KORE 4334.