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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIT Delhi |
The Syllabus
- Probability theory refresher
- Introduction to stochastic process
- Introduction to stochastic process (contd.)
- Probability theory refresher (contd.)
- Problems in random variables and distributions
- Problems in Sequence of random variables
- Definition and simple stochastic process
- Definition, classification and Examples
- Simple stochastic processes
- iscrete-time Markov chains
- Introduction, Definition and Transition Probability Matrix
- Chapman-Kolmogorov Equations
- Classification of States and Limiting Distributions
- Discrete-time Markov chains (contd.)
- Limiting and Stationary Distributions
- Limiting Distributions, Ergodicity and stationary distributions
- Time Reversible Markov Chain, Application of Irreducible Markov chains in Queueing Models
- Reducible Markov Chains
- Continuous-time Markov chains
- Definition, Kolmogrov Differential Equation and Infinitesimal Generator Matrix
- Limiting and Stationary Distributions, Birth Death Processes
- Poisson processes
- Continuous-time Markov Chains (contd.)
- M/M/1 Queueing model
- Applications of CTMC
- Queueing networks
- Communication systems
- Stochastic Petri Nets
- Martingales
- Conditional Expectation and filtration
- Definition and simple examples
- Brownian Motion
- Definition and Properties
- Processes Derived from Brownian Motion
- Stochastic Differential Equation
- Renewal Processes Renewal Function and Equation
- Generalized Renewal Processes and Renewal Limit Theorems
- Markov Renewal and Markov Regenerative Processes
- Non Markovian Queues
- Application of Markov Regenerative Processes
- Branching Processes
- Stationary and Autoregressive Processes
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