Courses that bridge theory and production.

DATA 5630 · developed from scratch · Spring 2023

Deep Forecasting — Advanced Time Series

Classical time series models meet modern machine learning and deep learning. Launched as a special topic; its success made it a permanent part of the curriculum.

Key areas

• Time series fundamentals and stationarity
• Exponential smoothing and ARIMA/SARIMA
• Machine learning for time series
• Deep sequence models (RNN/LSTM)
• Prophet, NeuralProphet, and AutoML tools
• Production-ready deployment

DATA 5600 · DAIS department · ongoing

Machine Learning

The foundational course of the Data Analytics track. Real-time coding sessions on Google Colab so concepts get applied — and tested — immediately.

Key areas

• Supervised and unsupervised learning
• Model evaluation and validation
• Feature engineering and selection
• Practical implementation, end to end

DATA 5610 · DAIS department · ongoing

Deep Learning

From fundamentals to the frontier: modern architectures for vision and sequence modeling, taught with working code.

Key areas

• Deep neural networks (NN, DNN)
• Convolutional networks (CNN, R-CNN, YOLO, FCN)
• Recurrent networks (RNN, LSTM)
• Transformers and attention

USU 1010 · first-year experience · Fall 2023

University Connections

Helping freshmen find their footing in college. Teaching this course keeps me close to the challenges new students actually face — and it shapes how I teach everything else.