Machine Learning

Machine Learning#

Course Description#

  • Course number: COMSC 335

  • Semester: Spring 2026

Machine learning is the study of creating programs that can learn through experience, and has become a powerful and pervasive paradigm in technology, science, and society. In this course, we will explore the mathematical foundations, methods, and practices that enable machine learning. Students will get hands-on experience understanding, building, and critically evaluating machine learning models using modern scientific computing frameworks coding in Python. This course is programming intensive and will have a substantial mathematical component.

Prerequisites#

  • COMSC 205: Data Structures

  • MATH 232: Discrete Math

  • A calculus course (ex: MATH 101, 102, or 203)

  • Familiarity with or a willingness to learn Python

When and Where#

  • When: Tuesdays and Thursdays, 1:45pm - 3:00pm

  • Where: Kendade 303

Teaching Staff#

  • Instructor: Tony Liu (he/him)

    • Office: Clapp 207

  • Teaching Assistant: Bhargavi Patil (she/her)

Acknowledgements#

This course would not be possible without a number of fantastic, freely available online resources, including:

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