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Advanced5 weeks

Reinforcement Learning

Train AI through rewards and experience

10 chapters
1 free chapters
4.9 rating

Course Curriculum

🔒 Full Course (9 chapters)

02
Markov Decision Processes
The math of RL
45 min
03
Q-Learning
Value-based methods
50 min
04
Policy Gradients
Learning policies directly
50 min
05
Actor-Critic Methods
Best of both worlds
45 min
06
Deep RL
Neural network RL
50 min
07
RLHF
Human feedback learning
45 min
08
Multi-Agent RL
Agents learning together
40 min
09
RL Applications
Games, robotics, more
45 min
10
Production RL
Deploying RL systems
40 min

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What You'll Learn

RL Fundamentals
Markov Decision Processes
Q-Learning
Policy Gradients
Actor-Critic Methods
Deep RL
RLHF
Multi-Agent RL

+ 2 more chapters

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