SSG 518
Machine Learning & AI
2
Course Description
At the end of this course, the students should be able to:
1. explain the use of AI as an intelligence augmentation tool;
2. discuss deep learning, its scope, achievements, limitations, and failures; and
3. use AI and ML software to augment intelligence and solve practical problems.
Course Outline
Introduction to search methods in Artificial Intelligence problems. Self-organizing systems.
Information theory, rational decision making and pattern recognition. Parametric and
nonparametric training for pattern classifiers. Problem solving. Minimax and alpha-beta
algorithm. Heuristic approaches to state-space search problems.
Prerequisite: SSG 311