Python is a popular programming language for analyzing numerical and textual data. The mini-course will present elements and features of Python and how it can be used within a workflow. The course includes hands-on exercises so participants can become familiar with programming techniques. The course is intended for researchers working with data generated by simulations, acquired from experiments, or collected from other sources.
Learning objectives: Emphasis on getting started with Python and understanding its fundamentals so attendees can continue learning on their own.
Knowledge prerequisites: Experience in another programming language is recommended background for the session.
Hardware/software prerequisites: We will use the Mac Pro workstations in the McGraw Center.
Workshop format: Presentation, demonstration, and class programming exercises.
Eliot Feibush is a Computational/Visualization Scientist. He specializes in developing scientific visualizations, frequently writing Python programs to select, analyze, convert, and display data from various applications and disciplines. Previously he has worked in medical imaging, architectural rendering, and geo-spatial analysis.