AOSC offers a 3 credit Scientific Programing: Python course (AOSC247) both Summer Session I and Spring semester. AOSC247 is a comprehensive Python programing course with no prior programing experience required. The course has three main educational goals.
- Python programming centered around scientific data analysis and visualization.
- Working with real world data sets, including the challenges real data presents.
- Mastering command line linux. Topics to include remote server access, text editing, directory structure, permissions, file transfer techniques, shell scripting, and data archiving.
From the Syllabus:
This is a comprehensive introductory course designed to prepare students to apply
scientific computation and visualization techniques in Python to data intensive questions
in the Natural Sciences. The class emphasizes real-world applications, providing students
with essential hands-on experience using Python for data analysis and visualization,
developing analytical skills for observational and modeling data, and performing virtual
experiments to distinguish data contributing factors. Students will also master the
command line Linux environment. Topics will include text editing, directory structure,
permissions, file transfer techniques, shell scripting, and data archiving.
This course has two overarching components: first, students will learn how to program with
Python, and second, students will learn statistical and spectral methods of analyzing data.
These two components will be bridged with homework plus exercise assignments utilizing
both mathematical and programming skills to examine Earth’s climate data, both observed
and modeled, accessible to the public. The analysis and programing skills learned can be
more generally applied to other scientific data with variations in time and/or space.
Students will use climate change data to explore signal vs noise, trend vs periodicity,
natural vs anthropogenic forcing, local vs remote response, mean vs extreme changes, and
accuracy vs uncertainty.