Semester:
Spring
Offered:
2025
CS 181 provides a broad and rigorous introduction to machine learning, probabilistic reasoning and decision making in uncertain environments. Students will derive the mathematical underpinnings for many common methods, work computationally, applying machine learning to challenges with real data, and give consideration to the ethical implications of machine learning. The material is aimed at an advanced undergraduate level and students should be comfortable with writing non-trivial programs, have a background in probability theory, and familiarity with calculus and linear algebra.