During the Fall 2022 semester, I had the opportunity to enroll in a graduate course called Applied Stochastic Processes at UC Berkeley. This course delved into applied topics within stochastic processes, making for a very intriguing learning experience. The primary concepts covered in the course included
- Conditional probability and expectation
- Discrete-Time Markov Chains and Continuous-Time Markov Chains
- The Poisson Process and Renewal Theory
- Applications to various stochastic systems like queueing systems, inventory models and reliability system
I've created a repository where I've uploaded my solutions to some interesting questions related to the course. Going forward, I plan to upload additional related materials when I have the time:)