Markov Decision Processes Courses and Certifications

Deep Reinforcement Learning - Frontiers - Lecture 18

Explore cutting-edge frontiers in deep reinforcement learning, covering problem setup, advanced methods, and real-world deployment strategies with Stanford's expert guidance.

• YouTube
• 1 hour 11 minutes
• Self-Paced
• Free Video

Deep Reinforcement Learning - Tutorial Session: Review of Q-Learning

Dive into Q-learning fundamentals with MDP review, parametric approaches, and practical algorithm walkthroughs for deep reinforcement learning mastery.

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

Artificial Intelligence - Principles and Techniques - Autumn 2019

Understand Artificial Intelligence, its principles and techniques with this Standford engineering course.

• YouTube
• 1 day 1 hour
• Self-Paced
• Free Online Course

University of Tübingen

Probabilistic Machine Learning

Comprehensive lecture series on probabilistic machine learning, covering Bayesian paradigms, statistical concepts, and deep learning connections for master's-level computer science students.

• YouTube
• 1 day 16 hours
• Self-Paced
• Free Online Course

Institute for Pure & Applied Mathematics (IPAM)

Quantum Algorithms for Scientific Computation Workshop 2023

Explore cutting-edge quantum algorithms for scientific computation, covering linear algebra, differential equations, and quantum simulation techniques from leading experts.

• YouTube
• 20 hours 58 minutes
• Self-Paced
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Reconstructing Network Dynamics from Data - Applications to Neuroscience and Beyond

Explore advanced mathematical techniques for reconstructing network dynamics from data, focusing on neuroscience applications and beyond through expert presentations.

• YouTube
• 15 hours 47 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

Inverse Methods in Heat Transfer

Discover advanced techniques for solving inverse heat transfer problems using regularization, Bayesian inference, and physics-informed neural networks.

• YouTube
• 1 day 6 hours 3 minutes
• Self-Paced
• Free Video

ANITI Toulouse

Reinforcement Learning Virtual School 2021

Dive into reinforcement learning fundamentals, deep Q-networks, policy gradients, and practical applications through this comprehensive virtual school from ANITI Toulouse.

• YouTube
• 1 day 12 hours 30 minutes
• Self-Paced
• Free Video

Serrano.Academy

A Friendly Introduction to Deep Reinforcement Learning, Q-Networks and Policy Gradients

Friendly exploration of deep reinforcement learning concepts, including Markov decision processes, Q-networks, and policy gradients, using examples and visuals to explain complex ideas.

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

Richard McElreath

Statistical Rethinking - Markov Chain Monte Carlo

Explore Markov chain Monte Carlo and Hamiltonian Monte Carlo methods, including practical implementation in Stan and diagnostic techniques for statistical modeling.

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

EuroPython Conference

Probabilistic Programming in Python

1 rating

Learn probabilistic programming in Python using PyMC3 for flexible statistical modeling, automated parameter estimation, and uncertainty quantification in data science and scientific research.

• YouTube
• 46 minutes
• Self-Paced
• Conference Talk

Conf42

Probabilistic Programming in Python - Conf42 Python 2024

1 rating

Explore Bayesian statistics, probabilistic modeling, and MCMC in Python. Learn key concepts and practical applications through demonstrations and workflow explanations.

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

Evolutionary Conundrums - Cooperation and Traversing Fitness Landscapes

Explore evolutionary biology: cooperation via social norms, fitness landscapes in rapidly evolving populations, and optimal antibiotic use against pathogens using Markov Decision Processes.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Dave Churchill

Introduction to Artificial Intelligence (2020-09)

Explore AI fundamentals through agents, search algorithms, game theory, genetic algorithms, reinforcement learning, and neural networks with hands-on programming assignments.

• YouTube
• 1 day 3 hours 4 minutes
• Self-Paced
• Free Video

IPhT-TV

An Introduction to Markovian Open Quantum Systems - 2017

Explore Markovian open quantum systems through comprehensive theoretical foundations and mathematical frameworks in this advanced physics lecture series.

• YouTube
• 9 hours 55 minutes
• Self-Paced
• Free Video