CSCI 175 - Introduction to Machine Learning and Artificial Intelligence

Credit(s): 4

This introductory course provides students with a foundational understanding of machinelearning (ML) and artificial intelligence (AI) concepts. Topics include supervised and unsupervised learning, fundamental ML algorithms, and an overview of AI applications across industries. Ethical considerations and the societal impact of AI will be explored to develop students’ awareness of responsible AI use. This course emphasizes practical applications, with hands-on projects using beginner-friendly tools.This introductory course provides students with a foundational understanding of machinelearning (ML) and artificial intelligence (AI) concepts. Topics include supervised and unsupervised learning, fundamental ML algorithms, and an overview of AI applications across industries. Ethical considerations and the societal impact of AI will be explored to develop students’ awareness of responsible AI use. This course emphasizes practical applications, with hands-on projects using beginner-friendly tools. (Fall Semester)

Course Learning Outcomes: Upon completion of the course, students will be able to

Explain foundational concepts and define terminology in machine learning and AI.
Identify and describe current AI capabilities and limitations.
Describe the differences and similarities of current AI services and platforms.
Demonstrate API integration and prompting.
Articulate potential societal impact and ethical considerations of AI technologies.
Implement integration projects using accessible tools.
Identify and describe historical developments and real-world application of AI.