More advanced ML courses (only offered some years):
- STAT542 - Bayesian Methods and Computation
- Shane Jenson on Bayesian methods (EM, Gibbs sampling)
- Multivariate methods
- Andreas Buja on multivariate methods (research oriented)
- STAT500 - Applied Regression and Analysis of Variance
- never underestimate the value of really understanding regression, but STAT 500 is too basic for people who have CIS520
- If you want the math side of regression, see STAT550 - Mathematical Statistics
- STAT553 - Machine Learning — probably too basic after 520
- STAT701 - Modern Data Mining — probably too basic after 520
Other related courses:
Many courses go into detail on applications of machine learning to e.g. vision or NLP
Again: there are also many options to do research in various labs around Penn.
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