Professional Certificate in Applied Bayesian Methods for Impact
-- ViewingNowThe Professional Certificate in Applied Bayesian Methods for Impact is a comprehensive course that equips learners with essential skills in Bayesian inference and modeling. This program is critical for professionals working in data science, machine learning, artificial intelligence, and related fields, where making informed decisions based on data is paramount.
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⢠Introduction to Bayesian Methods: Basic principles, advantages, and applications of Bayesian methods. Understanding probability from a Bayesian perspective.
⢠Probability Distributions: Overview of common probability distributions used in Bayesian analysis. Understanding the concept of conjugate priors.
⢠Bayesian Inference: Bayes' theorem, posterior distributions, and credible intervals. Computing and interpreting Bayes factors.
⢠Modeling with Stan: Introduction to Stan, a platform for Bayesian modeling. Writing and implementing Stan models for data analysis.
⢠MCMC Methods: Understanding Markov Chain Monte Carlo methods for sampling from posterior distributions. Comparing Gibbs sampling, Metropolis-Hastings, and Hamiltonian Monte Carlo.
⢠Model Selection and Comparison: Methods for comparing and selecting Bayesian models. Deviance Information Criterion, Leave-One-Out Cross-Validation, and Bayes factors.
⢠Bayesian Networks: Directed acyclic graphs, conditional probability distributions, and Bayesian networks. Application of Bayesian networks in decision making and risk analysis.
⢠Case Studies: Real-world examples of applying Bayesian methods to solve complex problems. Emphasizing practical skills for applying Bayesian methods in industry or research.
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