Overview
Description
This course explores the fundamental concepts of Artificial Intelligence (AI) and its applications in business. The course bridges the gap between theoretical AI concepts and practical applications by covering machine learning techniques, neural networks, deep learning models, and computer vision. Students will engage in a semester long hands-on project, discussions, and research that highlight the role of AI across industries.
Requirements
Prerequisites
IS 350
Original catalog text
Prerequisites
Prerequisite(s): IS 350
Units
Lecture3
Catalog Details
Offering
Offered: Every Fall and Spring
Terms
fall, spring
Attributes
Standard
Learning Outcomes
- explain fundamental AI concepts such as linear and logistic regression, neural networks, gradient descent, backpropagation, and model evaluation.
- design, train, and evaluate AI models for different applications.
- analyze and handle datasets effectively in AI experiments.
- evaluate real-world AI-powered products and assess their feasibility in business environments.
- describe ethical, cultural, financial, and technological implications of AI in business.