Lecture 1: Introduction to Markov Chains and CK equations
Lecture 2: Classification of states
Lecture 3: Stationary distributions and limiting distributions
Lecture 4: Limiting theorems for Markov chains
Lecture 5: Reversible Markov chains
Lecture 6: First step analysis
Lecture 7: Generating functions and branching processes
Lecture 8: Exponential distribution and Poisson process
Lecture 9: Thinning and superposition, variants of Poisson processes
Lecture 10: Continuous-time Markov chains
Lecture 11: Limiting probabilities
Lecture 12: Renewal processes and limit theorems
Lecture 13: Reward renewal processes and alternating renewal processes
Lecture 14: Inspection paradox and queueing models
Lecture 15: Other queueing models