Proposal Document: Creation of 100- and 200-Level Machine Learning and AI Courses at the Community College Level at Flathead Valley Community College

By James Goudy

Analysis in part by AI

Table Of Contents

1. Introduction: The Need for 100- and 200-Level Machine Learning (ML) and Artificial Intelligence (AI) Courses

As the fields of Machine Learning (ML) and Artificial Intelligence (AI) become increasingly integral to a wide array of industries, there is a pressing need to make foundational AI and ML education accessible to a broader student population. Currently, ML and AI courses offered in Montana are predominantly available at the university level, requiring advanced prerequisites in computer science, mathematics, and statistics. These courses primarily serve students already pursuing a computer science degree, often at junior or senior levels. This setup limits access for students who are at the beginning of their academic journey, as well as adult learners or working professionals interested in upskilling in these areas.

The introduction of 100- and 200-level ML and AI courses in community colleges aims to bridge this gap by providing accessible, practical, and ethically oriented training that meets the needs of entry-level learners. These courses will cater to a diverse student population, including recent high school graduates, those without prior experience in computer science, and working adults seeking new career paths. The focus on hands-on experience and real-world applications ensures that students gain job-ready skills applicable in various industries. Additionally, these courses will lay a foundation for students interested in furthering their studies at four-year institutions, creating a seamless pathway from community college to university-level AI and ML programs.

2. Course Titles, Descriptions, and Objectives for 100- and 200-Level ML and AI Courses

Course Title: Introduction to Machine Learning and Artificial Intelligence (100-Level)

Course Description: This introductory course provides students with a foundational understanding of machine learning (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.

Course Objectives:

1. Understand foundational concepts and terminology in machine learning and AI.
2. Gain awareness of historical developments and real-world applications of AI.
3. Explore basic ML algorithms, including their functions and uses.