This course offers a practical introduction to the key ideas and tools used in machine learning (ML). Students will learn how to work with data to make predictions, spot patterns, and solve common problems. The course covers various approaches, including methods for predicting outcomes and finding relationships in data, such as using decision trees and other simple techniques. In addition, students will explore how to recognize and address fairness and bias in machine learning, ensuring responsible and ethical use of these technologies. 202610.
Prerequisites: CAI 2000, COP 1000