coursework
Graduate coursework at Penn State.
| Course | Instructor | Topics |
|---|---|---|
| CSE 588: Large-Scale Machine Learning | Dr. Mehrdad Mahdavi | PAC learning, ERM, matrix computation, convex and non-convex analysis, gradient descent |
| IST 597: Fairness, Incentives, and Mechanism Design | Dr. Hadi Hosseini | Voting, resource allocation, matching |
| IST 597: Foundations of Deep Learning | Dr. C. Lee Giles | Neural networks, CNNs, RNNs and LSTMs, Transformers, physics-informed neural networks |
| IST 557: Data Mining I: Techniques and Applications | Dr. Justin Silverman | Linear and Bayesian regression, SVMs, clustering, ensembles, recommender systems |
| IST 558: Data Mining II | Dr. Justin Silverman | Bayesian statistics, MCMC, variational inference, generative models (VAEs, GANs) |
| STAT 500: Applied Statistics | Dr. Priyangi Bulathsinhala | Probability, distributions, hypothesis testing, confidence intervals, ANOVA |
| IST 504: IST Research Foundations | Dr. Luke Zhang | |
| IST 602: Supervised Experience in College Teaching | Dr. Lisa Lenze |