Temporal-Difference Learning Courses and Certifications

University of Alberta;  Alberta Machine Intelligence Institute

Sample-based Learning Methods

44 ratings

Explore sample-based learning methods in reinforcement learning, including Monte Carlo, temporal difference, and Dyna. Learn to estimate value functions, implement algorithms, and improve sample efficiency.

• Coursera
• 22 hours 16 minutes
• Self-Paced
• Paid Course

International Centre for Theoretical Sciences

N-Step Temporal Difference Learning with Optimal n

Explore n-step temporal difference learning algorithms and discover methods for determining optimal step sizes in reinforcement learning applications.

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

Steve Brunton

Q-Learning - Model Free Reinforcement Learning and Temporal Difference Learning

Explore Q-learning and temporal difference algorithms in reinforcement learning, including SARSA and connections to biological learning through dopamine. Covers key concepts for deep reinforcement learning.

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

Reinforcement Learning with Gymnasium in Python

Start your reinforcement learning journey! Learn how agents can learn to solve environments through interactions.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

HuggingFace

Temporal Difference Learning for Model Predictive Control - Research Presentation 3

Presentation on Temporal Difference Learning for Model Predictive Control, exploring innovative approaches in robotics and AI. Insights into recent papers and project developments by researcher Nicklas Hansen.

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

Dave Churchill

Introduction to Artificial Intelligence: Temporal Difference Learning - Lecture 17

Explore temporal difference learning, on/off-policy methods, and Q-learning. Gain hands-on experience with reinforcement learning algorithms through practical assignments and code examples.

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

Dave Churchill

Intro to Artificial Intelligence - Temporal Difference Learning - Lecture 19

Explore temporal difference learning and its applications in AI, focusing on practical implementations and problem-solving techniques.

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

Dave Churchill

Intro to Artificial Intelligence - Temporal Difference Learning - Lecture 18

Explore temporal difference learning and its applications in AI, with practical insights for Assignment 5 implementation.

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

Centre for Networked Intelligence, IISc

Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation: Tail Averaging and Regularization

Delve into advanced temporal difference learning analysis, exploring tail-averaging techniques and regularization methods for improved convergence rates in reinforcement learning applications.

• YouTube
• 1 hour 7 minutes
• Self-Paced
• Free Video

Dave Churchill

Intro to Artificial Intelligence - Temporal Difference Learning - Lecture 19

Explore temporal difference learning, SARSA, and Q-Learning algorithms with practical examples like the Cliff problem, plus guidance on Assignment 5 implementation for reinforcement learning applications.

• YouTube
• 1 hour 15 minutes
• Self-Paced
• Free Video

International Centre for Theoretical Sciences

Finite Time Analysis of Temporal Difference Learning with Linear Function

Explores finite time analysis of Temporal Difference Learning with linear function approximation, discussing probabilistic and optimization methods in data science and their applications.

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

International Centre for Theoretical Sciences

Finite Time Analysis of Temporal Difference Learning with Linear Function by L. A. Prashanth

Explore finite time analysis of Temporal Difference Learning with linear function approximation, examining theoretical foundations and practical implications for reinforcement learning algorithms.

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

Decision Making and Reinforcement Learning

25 ratings at Coursera

Explore sequential decision-making and reinforcement learning, covering utility theory, bandit problems, MDPs, POMDPs, Monte Carlo methods, and temporal difference learning. Gain practical skills through algorithms and examples.

• Coursera
• 1 day 23 hours 9 minutes
• Self-Paced
• Paid Course

Mastering Classic Reinforcement Learning Algorithms

Explore the mathematical foundations of reinforcement learning, covering Markov decision processes, dynamic programming, Q-learning, and SARSA to solve finite decision-making problems using tabular methods.

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

Career Certificate

Foundations of Reinforcement Learning

Explore reinforcement learning from classical foundations to deep learning methods and reward design, covering MDPs, Q-learning, neural networks, policy gradients, and safety-focused reward programming.

• Coursera
• Self-Paced
• Paid Course
• 3 courses