PREREQUISITES:
- Permission of Instructor
DESCRIPTION:
A comprehensive introduction to scientific computation and visualization techniques utilizing Python and FORTRAN to address data intensive questions in the Natural Sciences. The class emphasizes real-world applications, providing students with essential hands-on experience in data analysis and visualization, developing analytical skills for observational and modeling data, and performing virtual experiments to distinguish data contributing factors. Students will gain an understanding of the scientific data issues including: signal vs noise, trend vs periodicity, and accuracy vs uncertainty. Students will gain extensive experience using command line linux and utilizing common data formats such as HDF and netCDF. No prior programming experience required.