PHYS 4811 - Contemporary Applications of Physics: Machine Learning in Physics

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Course Description

Students in this course will apply the basic concepts of physics to the subject of machine learning. Topics include algorithms of supervised learning, unsupervised learning, and reinforcement learning, together with their applications in physics.

 

Teaching Pattern

  • Duration of course: about 4 weeks
  • Lecture hour(s) / Tutorial hour(s) per week: 3 

 

Content

This course introduces students to the fundamentals of machine learning and its applications in physics. Key topics include supervised learning, unsupervised learning, and reinforcement learning.

 

Remarks

  • Prerequisite(s): PHYS 2022 AND (PHYS 3142 OR MATH 3312) AND MATH 2023

 

Sample Course Outline