Model Based Reinforcement Learning Courses and Certifications

Yannic Kilcher

Mastering Atari with Discrete World Models - Machine Learning Research Paper Explained

Explore cutting-edge reinforcement learning with DreamerV2, a model-based AI agent achieving human-level performance on Atari games using discrete world models and latent space predictions.

• YouTube
• 55 minutes
• On-Demand
• Free Video

Simons Institute

Model-Based Reinforcement Learning with Value-Targeted Regression

Explore model-based reinforcement learning with value-targeted regression, covering episodic RL, UCRL, deterministic systems, and the MatrixRL algorithm.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Institute for Advanced Study

The Challenges of Model-Based Reinforcement Learning and How to Overcome Them - Csaba Szepesvári

Explore challenges in model-based reinforcement learning, including modeling errors and efficient planning, and discover strategies to overcome them in complex environments.

• YouTube
• 1 hour 39 minutes
• On-Demand
• Free Video

Pascal Poupart

Partially Observable RL

Explore partially observable reinforcement learning, covering Markov decision processes, hidden Markov models, and belief monitoring in this comprehensive lecture.

• YouTube
• 44 minutes
• On-Demand
• Free Video

Pascal Poupart

Model-Based RL

Explore model-based reinforcement learning, including complex models, Dyna algorithm, search trees, and Monte Carlo methods for effective planning and decision-making.

• YouTube
• 1 hour 25 minutes
• On-Demand
• Free Video

Stanford CS330: Deep Multi-Task and Meta Learning

Explore advanced machine learning techniques for efficient learning across multiple tasks, including optimization-based meta-learning, Bayesian approaches, and reinforcement learning applications.

• YouTube
• 18 hours
• On-Demand
• Free Online Course

Reinforcement Learning

This MOOC teaches the basics in reinforcement learning. It provides participants with a solid mathematical basis to study new methods from reinforcement learning research and put them into practice.

• edX
• 8 weeks, 2-3 hours a week
• On-Demand
• Free Online Course (Audit)

Open Data Science

Introduction to Reinforcement Learning

Explore reinforcement learning's evolution, breakthroughs, and applications in AI, from board games to robotics. Gain insights into key concepts, formulations, and future directions in this rapidly advancing field.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Video

Alexander Amini;  MIT

Generalizable Autonomy for Robot Manipulation

Explore generalizable autonomy in robot manipulation through imitation learning, visuo-motor policies, and reinforcement learning techniques. Discover innovative approaches for achieving adaptable and efficient robotic systems.

• YouTube
• 47 minutes
• On-Demand
• Free Video

Institute for Advanced Study

Deep Reinforcement Learning in the Real World - Sergey Levine

Explore deep reinforcement learning applications in real-world scenarios, focusing on off-policy methods, model-free and model-based approaches, and their practical implementations in robotics and manipulation tasks.

• YouTube
• 46 minutes
• On-Demand
• Free Video

Steve Brunton

Reinforcement Learning

Explora el Aprendizaje por Refuerzo, desde métodos básicos hasta redes neuronales y aplicaciones en dinámica de fluidos y control, en esta serie de 3.5 horas por Steve Brunton.

• YouTube
• 3 hours 30 minutes
• On-Demand
• Free Video

Edan Meyer

RL Foundation Models Are Coming!

Explore DeepMind's AdA algorithm, combining meta-learning, attention, and curriculum learning for advanced reinforcement learning. Discover promising results and future prospects in this emerging field.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Yannic Kilcher

Imagination-Augmented Agents for Deep Reinforcement Learning

Explore innovative deep reinforcement learning architecture combining model-free and model-based approaches for improved performance and efficiency in complex environments.

• YouTube
• 15 minutes
• On-Demand
• Free Video

Finnish Center for Artificial Intelligence FCAI

Hierarchical Imitation Learning with Vector Quantized Models

Learn hierarchical imitation learning techniques using vector quantized models for complex decision-making tasks, exploring subgoal identification and planning strategies to outperform expert demonstrations.

• YouTube
• 51 minutes
• On-Demand
• Free Video

Steve Brunton

SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning

Explores SINDy-RL, a framework combining sparse identification of nonlinear dynamics with reinforcement learning for efficient, interpretable control policies in complex environments.

• YouTube
• 21 minutes
• On-Demand
• Free Video