ITM 311 AI Fundamentals and Responsible Applications

This foundational course provides a comprehensive introduction to Artificial Intelligence (AI) and Machine Learning (ML) designed for students from all academic disciplines. It explores the historical development of AI, core terminology, and the principles behind major paradigms such as supervised, unsupervised, reinforcement, and generative learning. The course emphasizes practical accessibility, enabling students to experiment with widely used AI tools and frameworks to solve simple, domain-relevant problems. Students will also critically examine the ethical, legal, and societal implications of AI, including issues of bias, privacy, and accountability. Through a combination of lectures, hands-on exercises, and a culminating project, students will develop both conceptual understanding and practical experience, preparing them to apply AI responsibly in their fields of study. This course serves as the entry point for the AI Minor.

Credits

4

Prerequisite

Sophomore standing or higher.

Offered

fall semester