CS 470 — Introduction to Artificial Intelligence
Prerequisite: CS 312, 330
Introduction to core areas of artificial intelligence; intelligent agents, problem solving and search, knowledge-based systems and inference, planning, uncertainty, learning, and perception.
CS 478 — Introduction to Neural Networks and Machine Learning
Prerequisite: CS 252, 312
Neural network and machine learning models include Perceptrons, back-propagation, decision trees, genetic algorithms, and other mechanisms allowing computers to learn without being programmed.
URL: http://axon.cs.byu.edu/~dan/478/
CS 670 — Multi-Agent Systems
Prerequisite: CS 478 or equivalent
Introduction to fundamental concepts emphasizing current literature. Topics include gone theory, repeated play games, Arrow's impossibility theorem, negotiation, search, and learning.
CS 674 — Quantum Computation
Prerequisite: CS 252, 312, Math 343; or instructor's consent
Introduction to theory of quantum computing and its impact on science of computation. Introduces basic ideas in quantum information processing and focuses on quantum algorithms.
CS 678 — Advanced Neural Networks and Machine Learning
Prerequisite: CS 478 or equivalent
Advanced models, algorithms, and approaches in neural networks and machine learning.
URL: http://axon.cs.byu.edu/~martinez/classes/678
CS 778R — Topics in Neural Networks and Machine Learning
Prerequisite: CS 678
Advanced topics and readings in neural networks and machine learning.
URL: http://axon.cs.byu.edu/~martinez/classes/778
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