Monte Carlo Tree Search Courses and Certifications

Trelis Research

Improving LLM Accuracy with Monte Carlo Tree Search

Explore Monte Carlo Tree Search to enhance LLM accuracy, focusing on boosting Llama 3 8B performance. Learn implementation, testing, and limitations through code examples and mathematical problem-solving.

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

Discover AI

Scaling AI Reasoning: Monte Carlo Tree Search in In-Context Learning for Small Language Models

Explore advanced AI reasoning techniques through Monte Carlo Tree Search integration with In-Context Learning, enhancing small language models' cognitive capabilities and strategic decision-making.

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

Discover AI

AI Strategy Optimization Using Monte Carlo Tree Search - From Theory to Implementation

Explore Monte Carlo Tree Search algorithms and their application in AI decision-making, from basic principles to practical implementations in healthcare and financial forecasting.

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

Chris Hay

Write Your Own AI Agent with Monte Carlo Tree Search - Building a Tic-Tac-Toe Game

Master Monte Carlo Tree Search algorithm implementation by building a Tic-Tac-Toe AI agent, exploring its applications in modern AI systems like AlphaGo and O1 models.

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

Graham Neubig

Reward Models and Best-of-N - CMU LLM Inference 12

Explore reward models and best-of-n sampling techniques for optimizing LLM outputs, plus Monte Carlo Tree Search methods in this advanced NLP lecture.

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

Yannic Kilcher

Divide-and-Conquer Monte Carlo Tree Search for Goal-Directed Planning - Paper Explained

Explores a novel AI planning approach using divide-and-conquer Monte Carlo Tree Search, proposing intermediate goals to break complex problems into manageable sub-tasks for more efficient problem-solving.

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

Adversarial Search

1 rating at Udacity

Learn how to search in multi-agent environments (including decision making in competitive environments) using the minimax theorem from game theory. Then build an agent that can play games better than any human.

• Udacity
• 5 hours
• Self-Paced
• Paid Course

AlphaZero from Scratch – Machine Learning Tutorial

Build AlphaZero from scratch, mastering AI techniques for superhuman game play. Learn MCTS, neural networks, and self-play training to create powerful game-playing algorithms.

• freeCodeCamp
• 4-5 hours
• Self-Paced
• Free Video

GGP Course Videos

Comprehensive video series on General Game Playing, covering game description, management, playing strategies, and advanced topics like heuristic search and Monte Carlo methods.

• YouTube
• 3 hours 30 minutes
• Self-Paced
• Free Video

MLCon | Machine Learning Conference

How do Chess Engines Work - Looking at Stockfish and AlphaZero

Explore chess AI evolution: from Deep Blue's algorithms to Stockfish's Minimax, and AlphaZero's revolutionary self-learning approach using Monte Carlo Tree Search and neural networks.

• YouTube
• 1 hour
• Self-Paced
• Conference Talk

Sebastian Lague

Chess Programming Tournament Results and Analysis

Explore the fascinating world of chess programming as Sebastian Lague hosts a tournament, showcasing innovative bots, creative coding techniques, and thrilling matches.

• YouTube
• 1 hour 19 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

Churchill CompSci Talks

How Slot Machines Are Advancing the State of the Art in Computer Go AI

Explore Monte Carlo Tree Search in computer Go AI, covering its advantages, UCB1 strategy, and recent refinements like AMAF/RAVE, with insights into ongoing research topics.

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

Aleksa Gordić - The AI Epiphany

DeepMind's AlphaGo Zero and AlphaZero - RL Paper Explained

Explore DeepMind's revolutionary AI agents that mastered Go, Chess, and Shogi through self-play, without human knowledge. Learn about their inner workings, training process, and groundbreaking results.

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

Aleksa Gordić - The AI Epiphany

AlphaGo - Mastering the Game of Go with Deep Neural Networks and Tree Search - RL Paper Explained

Comprehensive exploration of AlphaGo's groundbreaking AI system, detailing its neural networks, search algorithms, and innovative techniques that led to defeating professional Go players.

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