Course description
This course explores the fundamentals of reinforcement learning (RL), including reward-based learning, policy optimization, and deep reinforcement learning using AI agents. Learn to design and train intelligent agents for gaming, robotics, and real-world applications.
What will i learn?
- Understand reinforcement learning principles and frameworks
- Train AI agents using Q-learning and policy optimization
- Implement deep reinforcement learning models
- Apply RL to robotics, gaming, and automation
Requirements
- Basic understanding of machine learning concepts
- Proficiency in Python programming
- Familiarity with neural networks (recommended)
Frequently asked question
AI enthusiasts, data scientists, and developers interested in reinforcement learning.
Basic knowledge of machine learning and Python is recommended.
RL fundamentals, AI agent training, Q-learning, policy optimization, and deep RL.
