Machine Learning Foundations

Catalog description

This course introduces the core concepts of machine learning, offering a comprehensive overview of the techniques and algorithms used in this rapidly growing field. Students will learn about the foundation of machine learning, including supervised and unsupervised learning, regression, classification, and clustering. Students will gain hands-on experience implementing machine learning algorithms using popular programming languages and libraries. Students also evaluate the ethical implications of AI solutions. Prerequisite/Corequisite: CIS 153 Python or permission of the instructor. Four lecture hours per week. An instruction support fee applies. General competencies met: Information Literacy. 4 Credits.