**INSTRUCTOR: PIERO BARALDI**

**LECTURES**

Lecture 1: Introduction

Lecture 2: Basic Notions of Probability Theory

Lecture 3 (Flipped): Discrete Random Variables (theory)

Lecture 3 (Flipped): Discrete Random Variables (exercise)

Lecture 4: Continuous Probability Distributions

Lecture 5: Reliability of Simple Systems

Lecture 6: Availability and Maintainability

Lecture 7: Markov Reliability and Availability Analysis: Discrete-time Markov Processes

Lecture 8: Markov Reliability and Availability Analysis: Continuous-time Markov Processes

Lecture 9: Monte Carlo Simulation for Reliability and Availability Analysis

Lecture 10: Monte Carlo Simulation for the Estimation of Definite Integrals

Lecture 11: Reliability Parameters Estimation: The Frequentist Approach

Lecture 12: Parameter Estimation: The Bayesian Approach

Lecture 13: Maintenance

Lecture 14: Probabilistic Risk Analysis

Lecture 15: Fault Tree Analysis

Lecture 16: Event Tree Analysis

Lecture 17: Dependent Failures

Lecture 18: Importance Measures

Lecture 19: Condition-Based Maintenance

**EXERCISES SESSIONS**

Exercise Session 1: Basics of Probability Theory

Exercise Session 2: Reliability of Simple Systems

Exercise Session 3: Markov Processes

Exercise Session 4: Monte Carlo Simulation

Exercise Session 5: Condition-Based Maintenance

Exercise Session 6: Estimation of Reliability Parameters

Exercise Session 7: Fault Tree Analysis

**EVALUATED GROUP EXERCISES**

Evaluated Group Exercise 1 – solution

Evaluated Group Exercise 2 – solution

Evaluated Group Exercise 3 – solution

Evaluated Group Exercise 4 – solution

Evaluated Group Exercise 5 – solution

Evaluated Group Exercise 6 – solution