Certificate in Bayesian Methods: Actionable Knowledge
-- ViewingNowThe Certificate in Bayesian Methods: Actionable Knowledge is a comprehensive course designed to empower learners with the essential skills needed to excel in today's data-driven world. This course focuses on Bayesian methods, a powerful and flexible framework for data analysis that is increasingly in demand across industries.
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โข Introduction to Bayesian Methods: Basic concepts, principles, and advantages of Bayesian methods. Understanding probability from a Bayesian perspective.
โข Probability Distributions: Overview of probability distributions, including normal, exponential, and beta distributions. Understanding conjugate priors.
โข Bayesian Inference: Bayes' theorem, posterior distributions, and credible intervals. Comparison with frequentist inference.
โข Model Specification and Fitting: Specifying models with prior distributions, model selection, and fitting models using Markov Chain Monte Carlo (MCMC) methods.
โข Model Checking and Criticism: Assessing model fit, diagnosing convergence, and model comparison techniques.
โข Hierarchical Models: Introduction to hierarchical models, including cross-level interactions and shrinkage. Applications in various fields.
โข Bayesian Computation: MCMC methods, including Gibbs sampling, Metropolis-Hastings algorithm, and Hamiltonian Monte Carlo. Understanding software tools like Stan and JAGS.
โข Case Studies: Real-world applications of Bayesian methods in various industries, such as finance, healthcare, and marketing.
โข Ethics and Bias: Addressing ethical considerations, potential biases, and limitations in Bayesian analysis.
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