ICS 652 Artificial Intelligence and Machine Learning
Artificial Intelligence (AI) is the field of studying the synthesis and analysis of computational agents that act intelligently. AI has several areas of study, such as Searching, Reasoning, Learning, and Knowledge Representation.
Searching helps the agent to reason and decide what to do, to determine the sequence of actions that will take to achieve its goals. Learning is the ability of the agent to improve its behavior based on experience. And knowledge representation is used to represent the individuals and the relationships between them, so the agent will be able to represent its own reasoning and use it to build knowledge¿ based systems.
This course focuses on searching algorithms, machine learning algorithms, and ontologies and knowledge¿based systems.
Prerequisites: Admission to Computer Science or Cybersecurity graduate program or instructor permission. Note: Students are responsible to both be aware of and abide by prerequisites for ICS courses for which they enroll, and will be administratively dropped from a course if they have not met prerequisites.
Special information
4 Graduate credits
Effective May 4, 2021 to present
Learning outcomes
General
- Examine the various types of searching algorithms.
- Compare and justify supervised learning, unsupervised learning, and reinforcement learning.
- Demonstrate the understanding of various optimization methods that are used in learning problems.
- Design OWL ontologies for knowledge representation and sharing.