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Reinforcement Learning
by Emma Brunskill · Stanford Online
4.7(1,500 reviews)
80K+ enrolled10 weeksUpdated 2024-04
What You'll Learn
Understand the fundamentals and key concepts of reinforcement learning
Apply reinforcement learning techniques to solve real-world problems
Understand the fundamentals and key concepts of MDPs
Apply MDPs techniques to solve real-world problems
Understand the fundamentals and key concepts of policy gradient
Apply policy gradient techniques to solve real-world problems
About This Course
Stanford course covering MDPs, policy search, model-based RL, exploration, and multi-agent reinforcement learning.
Curriculum
Module 1: Reinforcement learning & MDPs6 lessons
- Introduction to reinforcement learning
- Reinforcement learning in Practice
- Hands-on Exercise: Reinforcement learning
- Introduction to MDPs
- MDPs in Practice
- Hands-on Exercise: MDPs
Module 2: Policy gradient & Q-learning6 lessons
- Introduction to policy gradient
- Policy gradient in Practice
- Hands-on Exercise: Policy gradient
- Introduction to Q-learning
- Q-learning in Practice
- Hands-on Exercise: Q-learning
Module 3: Multi-agent RL3 lessons
- Introduction to multi-agent RL
- Multi-agent RL in Practice
- Hands-on Exercise: Multi-agent RL
Instructor
Emma Brunskill
Instructor at Stanford Online
Pros & Cons
Pros
- Highly rated by students
- Completely free to access
- High-quality video lectures
- Taught by Emma Brunskill
Cons
- No certificate provided
- Requires significant prior knowledge
- Self-paced requires discipline
Free
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