Fundamentals of Computational Science
Computational science lies at the intersection of the natural/social sciences, mathematics, and computer science. This course will teach students how to design and code Python programs to solve real-world problems. Using these programs, students will learn the core concepts of computational science, including the modeling process, methods of solving of simulating models using a computer, methods of statistical analysis for validating models, visualization techniques, and elements of good programming practice. Open source computational tools will be used.
Students who complete the course will be able to work through the process of designing, coding, and debugging a computer program; use a general approach to creating mathematical models in a variety of disciplines; map scientific or mathematical modeling problems to a computational framework; implement solutions or simulations of models using appropriate Python code; use basic statistical tools to assess reliability of models; use computer graphics tools to visualize model solutions or simulations; and collaborate successfully in a team working on a project.
Note: For successful completion of this course it is recommended that students have completed high school precalculus or equivalent.
Courses Include
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Lectures
How This Course Work
Courses are completely online: lectures, discussion boards, and even group projects.
You’ll be able to view course materials a full week before the class starts.
Once courses begin, assignments are due each week.
Need help or have questions? In addition to instructor access, every student receives support from an advisor.