Are you ready to explore the world of reinforcement learning (RL) and discover how intelligent systems make decisions?

This course will guide you from the fundamentals of RL—where agents learn and improve their behavior—right through to advanced, powerful techniques that drive real-world AI. You won’t just learn the “how” but also the “why” behind methods like Deep Q-Learning (DQN), Proximal Policy Optimization (PPO), and Actor-Critic models. These skills will let you create agents that can master games, navigate environments, and respond to changing surroundings.

With hands-on coding in PyTorch, you’ll apply these skills directly—building agents to balance poles, land lunar modules, and tackle real-time interactive challenges. By the end, you’ll have the confidence and knowledge to design, improve, and deploy your own intelligent agents.

Welcome to ROS2: Advanced Robotics Framework!

Master ROS2's real-time capabilities, robust communication, and advanced features like action servers and lifecycle management through hands-on projects.

This course equips you to build and manage complex robotic systems using C++ and Python, paving the way for innovation in modern robotics.