COS324:Introduction to Machine Learning

This course is a broad introduction to different machine learning paradigms and algorithms and provides a foundation for further study or independent work in machine learning and data science. Topics include linear models for classification and regression, support vector machines, clustering, dimensionality reduction, deep neural networks, Markov decision processes, planning, and reinforcement learning. The goals of this course are three-fold: to understand the landscape of machine learning, how to compute the math behind techniques, and how to use Python and relevant libraries to implement and use various methods.

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Semester: Fall24
Lectures: Monday,Wednesday 1:30 - 2:50
Location: Friend Center 101

Faculty

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Jia Deng
Office: Computer Science 423
Extension: 1203
Email: jiadeng
Additional Instructors: S. Caldas, A. Dieng

Additional Information

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Registrar's Fall24 COS offerings
CS Course Schedule
The Undergrad Coordinator is Colleen Kenny.
Email: ckenny
Office: Computer Science 210
Extension: 1746