Markov Processes (2025): Conditional Probability (Lecture 1)

It's 2025 and time for a new Markov Process series! This is mostly to replace the old one with better quality filming, sound, etc... It is the one I want to leave up for the duration as I phase the old videos, that were not filmed with intention, out. Although I am not looking back at my old videos, I am willing to bet that the first 10-15 videos here will be almost exactly the same content as before because foundation is foundation! As the semester progresses though, I expect the series to diverge. I've recently been tapped by Coursera to create a new Markov course (to launch on Coursera in Fall 2025) for people studying AI, so I'll be thinking a lot about that as I go here and you'll probably see AI-related examples/applications emerging in this series. Thanks for watching! 🔹Introduction 🔹 Definition of a Stochastic Process 1:35 🔹 Review of Conditional Probability (for events) 4:32 🔹 "Unraveling" Conditional Probability 16:12 🔹 Review of Conditional Probability (for random variables) 18:16 🔹 Definition of a Markov Process/Chain 35:50 🔹 Markov Chain Example 42:26