An introduction to problem-solving through computer programming with special focus on application to problems relevant to physics, chemistry, and biology. Students learn how to read, modify, design, debug, and test algorithms that solve problems. Programming concepts include control structures, problem solving strategies, abstraction, recursion, and modularity. Students explore these concepts in the context of interactive programs, data processing, and graphical and numerical analysis, using the Python programming language. Students are required to attend a 2.5-hour lab where they will apply concepts learned in lecture to study topics at the intersection of chemistry and physics. Topics might include: chemical kinetics, numerical integration, molecular dynamics, computational biology, Monte Carlo techniques, and basic statistical analysis.

Units: 1

Max Enrollment: 24

Prerequisites: MATH 115 and fulfillment of the Quantitative Reasoning portion of the Quantitative Reasoning and Data Literacy requirement. Prerequisites or Co-requisites - one of the following; ASTR 107, CHEM 105, CHEM 105P, CHEM 116 / BISC 116, CHEM 120, BISC 110, BISC111, BISC 112, BISC 113, GEOS 101, GEOS 102, NEUR 100, PHYS 100, PHYS 104, PHYS 106, PHYS 107, PHYS 108.

Instructor: Sandu, Teich

Distribution Requirements: MM - Mathematical Modeling and Problem Solving

Typical Periods Offered: Spring

Semesters Offered this Academic Year: Spring

Notes: