AI 250 Foundations of Artificial Intelligence (4 crs)

Prerequisite: DS 150 or CS 140, MATH 246 or MATH 345

Introduction to concepts related to the use and creation of AI. Students will gain an understanding of AI concepts and techniques, their ethical implications, explore transparency in AI models, and examine influence of AI on society and workforce.

Lecture/Discussion Hours: 4

Lab/Studio Hours: 0

AI 300 AI in Drug Design (3 crs)

Prerequisite: CHEM 105 or CHEM 151, and DS 150 or CS 140

The use of artificial intelligence in chemistry and biology including applications such as drug design. Integration of high-performance computing and computational methods to search, visualize, and analyze chemical and biological information. Discussion of key ethical concerns in informatics-based models.

Lecture/Discussion Hours: 3

Lab/Studio Hours: 0

AI 350 Human-Computer Interaction (4 crs)

Prerequisite: AI 250

Introduction to the design, implementation, and evaluation of interactive software and AI systems, with a focus on the intersection of ethics and computing. Topics include transparent and explainable AI, human abilities, user research, prototyping, evaluation techniques, design communication, and team skills.

Lecture/Discussion Hours: 4

Lab/Studio Hours: 0

AI 360 AI in Healthcare (3 crs)

Prerequisite: AI 250 or CS 255

This course explores the application of Artificial Intelligence (AI) in the healthcare industry, covering fundamental concepts, ethical considerations, and real-world applications. Students will gain an understanding of how AI is used in medical imaging, diagnostics, natural language processing, patient monitoring, and drug discovery.

Lecture/Discussion Hours: 3

Lab/Studio Hours: 0

AI 420 Artificial Intelligence (3 crs)

Prerequisite: AI 250. No credit if taken after CS 420.

A comprehensive exploration of Artificial Intelligence spanning classical to contemporary approaches. The course traces AI's evolution from symbolic reasoning and rule-based systems to current statistical and data-driven methodologies and examines crucial ethical considerations in AI, including data bias and societal impact.

Lecture/Discussion Hours: 3

Lab/Studio Hours: 0

AI 427 Natural Language Processing and Generative AI (3 crs)

Prerequisite: DS 250 OR CS 255

This course introduces students to the core principles and evolving landscape of Natural Language Processing (NLP). It begins with foundational techniques in text analysis and linguistic structures, providing a basis for understanding language data. Students will explore word representations and semantic models, progressing to cutting-edge architectures such as transformers and large language models.

Lecture/Discussion Hours: 3

Lab/Studio Hours: 0

AI 485 AI-Driven Project Development (3 crs)

Prerequisite: AI 250

An exploration of crafting intelligent software solutions using state-of-the-art AI techniques. Practical projects focus on designing, developing, and deploying AI-powered applications while applying the principles of the software development life cycle.

Grading Basis: A-F Grades Only

Lecture/Discussion Hours: 3

Lab/Studio Hours: 0