Hands-on introduction to scientific modeling and numerical simulations relevant to computational science and engineering. Students will learn how real-world problems can be solved using models, algorithms, and statistical tools. The course is organized around a set of team-based scientific computing projects drawn from various engineering and life science fields, using actual research and/or industrial computational codes. Leveraging simplified and user-friendly software interfaces and tutorials, the course focuses on the inductive learning of key concepts and topics such as physical and computational model formulation, verification and validation, uncertainty analysis, post-processing and data mining, and a high-level introduction to high performance computing. The course culminates with a community-engaged project, in which students are introduced to the basics of engineering design and team management to develop and animate a scientific computing activity in collaboration with, and tailored for, the Sciencenter. Future Science Leaders program for middle- and high-schoolers. No prior programming experience is necessary, and a high-school math level is assumed. Enthusiasm for computer-based activities and interest in community outreach is strongly recommended.

Outcome 1
Students will be able to understand "corner stone" skills of CSE, including modeling, code verification and validation, error analysis.

Outcome 2
Students will be able to create, use and manipulate software packages to learn how science problems can be represented in computational programs.

Outcome 3
Students will be able to be confident in their ability to use computers to solve scientific and engineering problems.

Outcome 4
Students will be able to learn practical skills to improve their ability to lead a team, be a good teammate and communicate effectively.