Markov Decision Processes Courses and Certifications

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

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

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

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

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

Fields Institute

MCMC Training of Bayesian Neural Networks

Explore Bayesian Neural Networks, MCMC methods, and their applications in machine learning with Prof. Radford Neal. Gain insights into flexible modeling and practical implementations.

• YouTube
• 1 hour 9 minutes
• Self-Paced
• Free Video

Strange Loop Conference

Training an Autonomous Pentester with Deep RL

Explore deep reinforcement learning for autonomous pentesting, using Metasploit and simulated networks to train an AI agent capable of compromising real-world vulnerable systems.

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

Simons Institute

Sampling Crash Course

Explore geometric methods in optimization and sampling, covering direct methods, Markov chain Monte Carlo, and probabilistic approaches for efficient algorithm design and analysis.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video