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Background and Motivation

• Lecture 1 (PDF)

Fundamental Model Development

• Lecture 2: Spring, rod and beam models (PDF)

Numerical Methods for ODE

• Lecture 3: Numerical methods for IVP and BVP (PDF)

Verification Techniques for ODE

• Lecture 4: Convergence analysis for IVP (PDF)
• Lecture 5: Convergence analysis for BVP (PDF)

Numerical and Verification Techniques for PDE

• Lecture 6: Numerical Techniques for PDE (PDF)
• Lecture 7: Verification Techniques for PDE (PDF)

Parameter Estimation Issues

• Lecture 8: Deterministic parameter estimation (PDF)
• Lecture 9: Statistical parameter estimation (PDF)

Propagation of Parameter Uncertainty in Models

• Lecture 11: Model uncertainty (PDF)

Model Validation Techniques

• Lecture 12: Validation using propagation of uncertainty (PDF)

Stochastic Models, Estimators and Emulators

• Lecture 13: Kalman Filters (PDF)

Fundamental Probability and Statistics Theory