One-Week Course in Uncertainty Quantification The one-week course in UQ covers the basics of uncertainty representation and propagation, as well as statistical inference. The course starts with sampling-based techniques for handling probabilistic uncertainty, interval uncertainty, and mixed uncertainty forms. Mixed uncertainty techniques are based in credal set theory and random set theory (i.e. Dempster-Shafer theory). The course then proceeds to deal with parameter inference, exploring both traditional Bayesian and advanced frequentist approaches. Finally, different approaches to statistical testing are introduced, as a way to deal with complex hypotheses. 

The complete syllabus is attached

Two-Week Course in V&V&UQ, for Engineers The two-week course in V&V&UQ for engineers covers all of the material offered in the one-week course in UQ, albeit at a more relaxed pace. Fundamental approaches to model validation and computational verification are also taught. The validation material focuses on quantifying model form uncertainty using experimental data. The verification material focuses on convergence issues that accompany the finite solutions to partial differential equations. 

The complete syllabus is attached

Two-Week Course in V&V&UQ, for Finance The two-week course in V&V&UQ for practitioners in finance covers all of the material offered in the one-week course in UQ, albeit at a more relaxed pace. Fundamental approaches to model validation , computational verification, and data mining are also taught. The validation material focuses on quantifying model form uncertainty using historical data. The verification material focuses software quality control practices and version control and is foreshortened relative to the verification material taught in the engineering version of the course. In its place, time is spent on methods used to help build models in the first place. 

The complete syllabus is attached

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Michael Balch,
Jul 7, 2015, 3:13 PM
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Michael Balch,
Jul 7, 2015, 3:13 PM
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Michael Balch,
Jul 7, 2015, 3:13 PM