Undergraduate Certificate in Practical Bayesian Inference for AI Engineering
-- ViewingNowThe Undergraduate Certificate in Practical Bayesian Inference for AI Engineering is a crucial course that focuses on enhancing learners' understanding of Bayesian inference and its applications in Artificial Intelligence (AI). This certificate course is essential in today's data-driven world, where AI is becoming increasingly important in various industries.
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โข Introduction to Bayesian Inference: Basic concepts, principles, and advantages of Bayesian inference
โข Probability Theory: Probability distributions, joint, marginal, and conditional probability
โข Bayes' Theorem: Understanding and applying Bayes' theorem in practical situations
โข Graphical Models: Directed acyclic graphs, plate notation, and their role in Bayesian inference
โข Conjugate Priors: Identifying and using conjugate prior distributions
โข Markov Chain Monte Carlo: Sampling techniques, Metropolis-Hastings algorithm, and Gibbs sampling
โข Hierarchical Models: Structuring complex models using multiple layers of random variables
โข Model Selection and Evaluation: Deviance information criterion, cross-validation, and predictive accuracy
โข Bayesian Networks: Construction, inference, and learning in Bayesian networks
โข Applications in AI Engineering: Bayesian methods in machine learning, decision making, and reinforcement learning
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