Anastasiya Protasov

Modeling, Simulation, and Visualization using Matlab and Python. This project-based course introduces students to engineering computation in Matlab and Python. Computational projects motivated by different science and engineering applications are used to introduce basic numerical methods, and develop computational solutions using Matlab and Python. No programming knowledge is required or expected; students learn how to implement their solutions in Matlab and Python. Lectures are held Mondays and Wednesdays. In a laboratory component held on Fridays, students work in small groups on computational projects led by a Rice Learning Assistant. Fall/Spring semester: meeting 3 times per week (50min each meeting). Summer semester: meeting 5 times per week (65min each meeting) OR refer to the current schedule. Cross-list: CMOR 220, CMOR 220, CMOR 220, CMOR 220, CMOR 220, CMOR 220, CMOR 220, CMOR 220. Recommended Prerequisite(s): MATH 101 or MATH 105

This course is designed to support Rice Learning Assistants (RLAs) as they instruct their own lab sections of CMOR 220. Topics include analysis of computational science and engineering concepts, issues of problem-based learning (PBL), theories of learning, and fundamental teaching skills. Required for CMOR 220 RLAs. Repeatable for Credit.

Introduction to fundamental tools in computational mathematics and their application to science and engineering problems using Python. Topics include tools from linear algebra for data compression, least squares, and dynamical systems; modeling and simulation using ordinary differential equations; approximation and interpolation of functions; gradient-based methods for parameter estimation.