Data Science in Physics
Aims to present modern computational methods by providing realistic, contemporary examples of how these computational methods apply to physics research. Designed around research modules in which each module provides experience with a specific scientific challenge. Modules include: analyzing LIGO open data; measuring electroweak boson to quark decays; understanding the cosmic microwave background; and lattice QCD/Ising model. Experience in Python helpful but not required. Lectures are viewed outside of class; in-class time is dedicated to problem-solving and discussion. Students taking graduate version complete additional assignments.
Prerequisites & course information
Subject meets with 8.16 Prereq: 8.04 and ( 6.100A , 6.100B , or permission of instructor) G (Spring) 3-0-9 units
Sources
- Course catalogue ↗2026–2027