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