Python is a versatile and powerful general-purpose programming language, and people with a broad spectrum of skills use it for their research and work. Handling data in Python is sometimes challenging in terms of working with large datasets and efficient parsing of data files. In this course, we'll go deep in Python and best practices when working with datasets and especially tools for handling large datasets. We cover intermediate to advanced topics from data structures to working efficiently with data files.

Audience: University-wide
Pre-Requisites: Basic familiarity with Python is required. Participants should be able to use an integrated development environment (IDE) or a command-line text editor, such as Vim/Nano/Emacs, without assistance.
Cost: None
Late Drop/Cancel Fee: None

Additional Information: Since students and researchers will utilize the FAS Research Computing CANNON cluster to run the Python codes, basic familiarity with the CANNON, Python, and Unix commands is strongly recommended. Otherwise, attendees will not be able to keep up during the workshop's hands-on part.

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