The Python software ecosystem provides a rich collection of tools and packages, developed by many programmers with expertise in different areas, that support computation in many different application areas. The Python ecosystem is especially useful in empowering researchers and developers in the areas of computational science, data science, and machine learning, and has long been embraced by people working on such problems. This lecture will provide a broad overview of some of the key components of the Python software stack that provide support for numerical computing, scientific algorithms, data processing, data visualization, and machine learning, along with some examples of their use.

Instructor: Chris Myers, Cornell University Center for Advanced Computing

Prereqs: Some familiarity with the Python programming language or other languages used for scientific computing (e.g., R, MATLAB) would be useful, but is not required.

For more information or to register, go to: https://its.weill.cornell.edu/scientific-computing-training-series