CIS 117 - AI Agents

Credit(s) 2.00
Lecture Hours: 2.00
This course introduces the design and development of autonomous AI agents that perceive, reason, and act within digital or physical environments. Students explore intelligent agent architectures, the foundations of reinforcement learning, and multi-agent collaboration. Emphasis is placed on the hands-on development of functional agents, such as chatbots, task automation bots, and interactive systems, using modern Python frameworks. Ethical and operational considerations of deploying autonomous systems are also examined. No

Prerequisite(s):

CIS 107

SLOs:
Upon successful completion of this course, students will be able to:

Define the components, structure, and classifications of AI agents.
Design a functional autonomous agent for a defined purpose.
Implement a functional autonomous agent for a defined purpose.
Apply reinforcement learning techniques to modify agent behavior through experience.
Evaluate performance, reliability, and ethical implications of AI agents in real-world use cases.