Computing and Data Analysis for the Sciences
Scientific computing emphasizes data analysis and visualization in a scientific context - analyzing data quickly for understanding by the individual, sharing automated workflows with collaborators, and preparing results for later publication. This course will emphasize rapid, interactive, and reproducible collaborative analysis of data for scientific contribution.
Students are required to have taken MATH 117: College Algebra as a prerequisite or to have been placed in MATH 118: Precalculus or higher.
At the end of this course, students will be well versed in the use of a specific, interactive environment for data analysis (likely Python, R, or MATLAB as indicated in the course notes) for analyzing data and sharing results.
Students are required to have taken MATH 117: College Algebra as a prerequisite or to have been placed in MATH 118: Precalculus or higher.
At the end of this course, students will be well versed in the use of a specific, interactive environment for data analysis (likely Python, R, or MATLAB as indicated in the course notes) for analyzing data and sharing results.