Faculty Name: Dr. Srijith P.K

Course Name: Bayesian Data Analysis

Course Period: 06 ^th Jan to 30 ^th Apr 2025 (Tuesday 02:30 PM to 03:55 PM; Friday 04:00 PM to 05:25 PM)

Number of Credits: 2 credits

Course Contents: The course will tentatively cover various topics on Bayesian data analysis such as

1. Maximum Likelihood (ML), maximum a-posteriori (MAP) and Bayesian estimation of single and multi-parameter models.
2. Bayesian machine leaning approaches such as Bayesian linear regression, Bayesian Naïve Bayes Classifier, Bayesian logistic regression, Bayesian gaussian mixture modelling, latent Dirichlet allocation.
3. Hierarchical modelling, Model selection.
4. Inference algorithms based on Monte Carlo methods, Laplace approximation, variational inference, and expectation propagation.
5. Bayesian non-parametrics (Gaussian Processes, Dirichlet Processes)
6. Bayesian deep learning (Bayesian neural networks, variational auto-encoders, diffusion models)
7. Bayesian optimization