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AISE 4030A/B

REINFORCEMENT LEARNING

0.50 credits

Reinforcement Learning (RL) is a field of AI where agents learn to make decisions through trial-and-error to maximize rewards. This course covers core RL concepts, algorithms, and applications, including Q-Learning, Deep RL, and policy-based methods, with hands-on experience to solve real-world problems in robotics, games, and recommendation systems.

Prerequisites & course information

Prerequisite(s): Data Science 3000A/B and ( NMM 2276A/B or NMM 2277A/B ). Extra Information: 3 lecture hours. Course Weight: 0.50

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