Markov Chains Courses and Certifications

Discrete-Time Markov Chains and Monte Carlo Methods

20 ratings at Coursera

Compute transition matrices, limiting and stationary distributions, and first-step analyses for Markov chains, then simulate with accept-reject, Metropolis-Hastings, Gibbs sampling, and Markov decision processes.

• Coursera
• 6 weeks, 5 hours a week
• Self-Paced
• Paid Course

Queuing Theory: from Markov Chains to Multi-Server Systems

13 ratings

Learn key mathematical tools necessary to anticipate the performance levels of queueing systems and understand the behavior of other systems that evolve randomly over time.

• edX
• 5 weeks, 3-4 hours a week
• Self-Paced
• Free Certificate

Valerio Velardo - The Sound of AI

Markov Chains for Generative Music AI - Lecture 11

Explore Markov chains for generative music AI, covering intuition, formalization, music modeling, pros and cons, and practical applications in melody, rhythm, and dynamics generation.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

The Birth-Death Continuous Time Markov Chains - Lecture 74

Explore continuous time birth-death Markov chains, analyzing expected waiting times and queue lengths in various queueing systems.

• YouTube
• 19 minutes
• Self-Paced
• Free Video

UofU Data Science

Data Mining: Markov Chains for Graphs - Lecture 22

Explore the modeling of graphs as Markov Chains, including concepts of ergodicity, limiting state vectors, and delicate balance in this data mining lecture.

• YouTube
• 1 hour 23 minutes
• Self-Paced
• Free Video

UofU Data Science

Markov Chains - From Probability Transition Matrix to Ergodic Properties and Algorithms - L24

Explore Markov chains through probability transition matrices, ergodic properties, and limiting states. Master 4 key algorithms including eigenvalue methods and random walks for data science.

• YouTube
• 1 hour 23 minutes
• Self-Paced
• Free Video

Wolfram

Games with Markov Chains or Intransitivity - Episode 38

Explore mathematical games featuring Markov chains and intransitive relationships with expert Ed Pegg Jr. in this engaging 70-minute session from Wolfram.

• YouTube
• 1 hour 10 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Matrix Representation of a Discrete-Time Markov Chain (DTMC) - Lecture 46

Explore matrix notation of DTMCs, including egodicity, ergodic chains, and global balance equations. Learn about n-step transition probabilities in this concise lecture.

• YouTube
• 15 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Stationary Distribution of a Markov Chain

Explore the concept of stationary distribution in Markov chains, understanding its properties and applications in probability theory and stochastic processes.

• YouTube
• 18 minutes
• Self-Paced
• Free Video

patrickJMT

Markov Chain

Explore transition diagrams, steady states, regular Markov chains, and absorbing chains through applied problems.

• YouTube
• 1 hour 30 minutes
• Self-Paced
• Free Video

Introduction to Renormalization

12 ratings

This tutorial provides a modern introduction to renormalization from a complex systems point of view.

• Complexity Explorer
• 1 hour
• Self-Paced
• Free Certificate

Algorithmic Composition - Markov Chains and Music21 Chord Analysis - Class 23

Explore algorithmic composition techniques using Markov chains and Music21's Chord and Roman Numeral tools for computational music creation.

• YouTube
• 52 minutes
• Self-Paced
• Free Video

Valerio Velardo - The Sound of AI

Melody Generation with Markov Chains - Generative Music AI

Implement a Markov chain in Python to generate melodies, exploring the MarkovChainMelodyGenerator class, training process, and generation methods for AI-driven music creation.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

Confreaks

LabVIEW Autocomplete - Converting Block Diagrams to Directed Graphs and Markov Chains

Discover how to build LabVIEW autocomplete using directed graphs and Markov chains to predict code blocks, with live demos and practical implementation insights.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

Advanced Probability and Statistical Methods

Work through joint distributions, expectation and covariance, the Markov and Chebyshev inequalities, the central limit theorem, hypothesis testing and Markov chains, implementing methods in R.

• Coursera
• 6 weeks, 8 hours a week
• Self-Paced
• Paid Course