2025-2026 Academic Catalog 
    
    Jun 27, 2025  
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2025-2026 Academic Catalog

MSAI 3120 - Reinforcement Learning

This course explores the principles and applications of reinforcement learning (RL), a machine learning paradigm where agents learn by interacting with their environment to maximize cumulative rewards. Students will learn the fundamentals of RL algorithms, such as Q-learning, deep Q-networks (DQNs), policy gradients, and actor-critic methods. The course emphasizes practical implementation through Python and frameworks such as  OpenAI  Gym  and  TensorFlow.  Applications  include  generative  models,  game  AI, robotics, and real-world decision-making systems. Special attention is given to the role of RL  in  generative  AI,  including  its  use  in  optimizing  content  generation  and  adaptive systems.

Prerequisites: MSDA 3050 - Applied Machine Learning  

Anticipated Terms Offered: each semester
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