1. Random numbers (Monte Carlo tecniques) 
1.1 Probability and inference refresher
1.2 Statistical validation techniques
1.3 (Pseudo)random number generation
1.4 Approximation of probabilities and volumes
1.5 Monte Carlo integration
2. Simulating random variables and vectors
2.1 Inverse transform
2.2 Aceptance-rejection
2.3 Composition approach
2.4 Multivariate distributions
2.5 Multivariate normal distribution
3. Discrete event simulation
3.1 Poisson processes
3.2 Gaussian processes
3.3 Single- and multi-server Queueing systems
3.4 Inventory model
3.5 Insurance risk model
3.6 Repair problem
3.7 Exercising a stock option
4. Efficiency improvement (variance reduction) techniques
4.1 Antithetic variables
4.2 Control variates
4.3 Stratified sampling
4.4 Importance sampling
5. MCMC
5.1 Markov chains
5.2 Metropolis-Hastings
5.3 Gibbs sampling
6. Introduction to the bootstrap
6.1 The bootstrap principle
6.2 Estimating standard errors
6.3 Parametric bootstrap
6.4 Bootstrap Confidence Intervals
6.5 Bootstrap Hypothesis Tests