Discrete-time Markov Chains and Poisson Processes free videos and free material uploaded by Guwahati Staff .
Week 1:Introduction to Discrete-time Markov Chains
Week 2:Communication
Week 3:Hitting Times
Week 4:Classification of States
Week 5:Stationary Distribution
Week 6:Limit Theorems
Week 7:Exponential Distribution and Counting Processes
Week 8:Poisson Processes
In this course we will cover discrete-time Markov chains and Poisson Processes. Knowledge of calculus and basic probability is essential for this course. The mathematical rigor of the course will be at an undergraduate level. We will cover from basic definition to limiting probabilities for discrete -time Markov chains. We will discuss in detail Poisson processes, the simplest example of a continuous-time Markov chain. The course will involve a lot of illustrative examples and worked out problems.
PRE-REQUISITE : Basic Probability,Calculus
INDUSTRY SUPPORT : Supply Chain, Communications.
INTENDED AUDIENCE : Undergraduate students of Science and Engineering. Many postgraduate students as well as industry professionals dealing with stochastic modelling may find the course useful.
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