Deep Q Networks Courses and Certifications

Edan Meyer

Q-Learning Tutorials - Deep Q Networks, Experience Replay, and Advanced Architectures

Master Q-Learning fundamentals through Deep Q Networks, experience replay, training loops, and advanced architectures like double and dueling networks.

• YouTube
• 2 hours 22 minutes
• Self-Paced
• Free Video

Deep Reinforcement Learning in Python

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

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

Pascal Poupart

Deep Q-Networks

Learn advanced reinforcement learning techniques, focusing on Deep Q-Networks. Explore approximation, optimization, and practical implementations to enhance AI decision-making capabilities.

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

Packt Credential

Deep Reinforcement Learning Hands-On

Master Deep Reinforcement Learning from foundations to cutting-edge topics, covering PyTorch, DQN, Actor-Critic Methods, robotics, and multi-agent RL for real-world applications.

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

Packt

Advanced Deep RL Algorithms and Applications

Master advanced deep RL algorithms—DQN extensions, policy gradients, and actor-critic methods—applying them to gaming, stock trading, and NLP environments to solve complex real-world AI challenges.

• Coursera
• 7 hours
• Self-Paced
• Paid 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

Pascal Poupart

Deep Recurrent Q-Networks

Explore deep reinforcement learning with recurrent neural networks, focusing on LSTM units, Q-learning, and their applications in sequential decision-making problems.

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

Yannic Kilcher

Q-Learning: From Basics to Deep Q-Networks

Explore Q-Learning fundamentals, from Markov Decision Processes to Deep Q-Networks, in this comprehensive overview of reinforcement learning concepts and applications.

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

IIT Madras;  NPTEL

Reinforcement Learning

Explore mathematical foundations and recent research in trial-and-error learning, covering bandit algorithms, MDPs, dynamic programming, function approximation, and advanced topics like hierarchical RL and POMDPs.

• Swayam
• 12 weeks
• Self-Paced
• Free Online Course

Python Reinforcement Learning using OpenAI Gymnasium – Full Course

Comprehensive guide to reinforcement learning using Gymnasium, covering basics, implementation in Blackjack and Cartpole environments, and advanced topics like multi-agent systems and Deep Q-Networks.

• freeCodeCamp
• 2-3 hours
• Self-Paced
• Free Video

Alexander Amini;  MIT

Reinforcement Learning

Explore deep reinforcement learning concepts, from Q-functions to policy gradients, with applications in Atari games, real-world scenarios, and groundbreaking AI like AlphaGo.

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

Pascal Poupart

Reinforcement Learning - Spring 2018

Master reinforcement learning algorithms that enable machines to learn from partial feedback, covering Markov processes, deep RL, bandits, and applications in robotics and games.

• YouTube
• 1 day 22 minutes
• Self-Paced
• Free Video

CodeEmporium

Reinforcement Learning 101

Discover the fundamentals of reinforcement learning through multi-armed bandits, Q-learning, deep Q-networks, and policy optimization techniques used in modern AI systems.

• YouTube
• 2 hours 4 minutes
• Self-Paced
• Free Video

Python Lessons

Reinforcement Learning - From DQN to PPO with Practical Applications

Master advanced reinforcement learning algorithms from DQN to PPO, building AI agents that play games, land rockets, and navigate complex environments through hands-on projects.

• YouTube
• 7 hours 59 minutes
• Self-Paced
• Free Video

Alexander Amini;  MIT

MIT: Reinforcement Learning

Explore deep reinforcement learning concepts, algorithms, and real-world applications in this comprehensive lecture from MIT's Introduction to Deep Learning course.

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