Markov Chains Courses and Certifications

Data Science Decisions in Time: Using Data Effectively

Program optimal decisions on sequential data streams using Wald's sequential analysis, Thompson sampling, change point detection, Markov chains, and Markov decision processes.

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

Career Certificate

Foundations of Probability and Statistics

369 ratings at Coursera

Build a mathematical foundation for data science and AI: quantify uncertainty with random variables, model systems with discrete-time Markov chains, and construct maximum likelihood estimators.

• Coursera
• 12 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 3 courses

Mastering Classic Reinforcement Learning Algorithms

Formulate decisions as finite Markov decision processes and solve them with value iteration, policy iteration, bandits, Monte Carlo methods, temporal-difference learning, SARSA, and Q-learning.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

Engineering Genetic Circuits: Abstraction Methods

Abstract genetic circuit models using steady-state reaction-based approximations, piecewise linear representations, Markov chain analysis, state-based abstraction, and infinite-state stochastic model checking of circuit hazards.

• Coursera
• 5 weeks, 4 hours a week
• Self-Paced
• Paid Course

Introduction to Probability

42 ratings at edX

Learn probability, an essential language and set of tools for understanding data, randomness, and uncertainty.

• edX
• 10 weeks, 5-10 hours a week
• Self-Paced
• Free Online Course (Audit)

Quantitative Model Checking

54 ratings at Coursera

Verify dependable systems formally: model them as labeled transition systems and discrete- and continuous-time Markov chains, then model check CTL, PCTL, and CSL properties.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

Probabilistic Systems Analysis and Applied Probability

A course on the modeling and analysis of random phenomena and processes, including the basics of statistical inference.

• MIT OpenCourseWare
• 21 hours
• Self-Paced
• Free Video

Probabilistic Systems Analysis and Applied Probability

This course introduces students to the modeling, quantification, and analysis of uncertainty.

• MIT OpenCourseWare
• 32 hours
• Self-Paced
• Free Video

Discrete Stochastic Processes

This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of Discrete stochastic processes.

• MIT OpenCourseWare
• 33 hours
• Self-Paced
• Free Video

Introduction to Probability

An introduction to probability from axioms and random variables through Bayesian inference, limit theorems, Poisson processes, and Markov chains.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Coding Train

Programming with Text - Complete Course Series

Master text manipulation, regular expressions, natural language processing, and API development through hands-on JavaScript projects and creative coding challenges.

• YouTube
• 16 hours 53 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Introduction to Continuous Time Markov Chains - Lecture 67

Explore continuous time Markov chains, embedded DTMC, and M/M/1 Queue concepts to enhance your understanding of stochastic processes and queueing theory.

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

Mathematical understanding of uncertainty

This lecture series discusses how the concept of probability can be used to handle, control, and exploit uncertainty in the real-world. It is an undergraduate-level lecture series on probability, but

• edX
• 12 weeks, 1-2 hours a week
• Self-Paced
• Free Certificate

IIT Delhi;  NPTEL

Introduction to Probability Theory and Stochastic Processes

Build probability foundations and study stochastic processes through distributions, convergence, Markov chains, and simple Markovian queueing models.

• Swayam
• 12 weeks
• Available until Oct 9, 2026
• Free Online Course

Introduction to Finite Mathematics Online Video Course: Wolfram U

Review elementary algebra and apply it to linear systems, matrices and optimization, then work through the mathematics of finance, probability, Bayes' theorem, Markov chains and game theory.

• Wolfram U
• 6 hours
• Self-Paced
• Free Certificate