Scientific Computing Training Series - Scientific Computing with Python (with hands-on)

Description: This intermediate-level webinar will provide an overview of select core components of the Python software ecosystem for scientific computing and data science, with a particular focus on numpy, scipy, pandas, and matplotlib. It will include both descriptions of the overall design and structure of those packages and their key components and numerous code examples that demonstrate some of the important functionality. Opportunities for live, hands-on exercises using these packages will be integrated throughout the lecture, all as part of a Jupyter Notebook that will include both the lecture content and the hands-on exercises. The Python ecosystem for scientific computing and data science ecosystem enables researchers to use proven and widely used tools that are easily customized for specific problems using the Python programming language. Prerequisites: Some familiarity with the Python language or other languages used for scientific computing (e.g., R, MATLAB) would be useful, but is not required. The hands-on exercises will be coordinated through the use of an online cloud computing environment providing support for running Jupyter Notebooks, although participants should feel free to use their own local machines if they are familiar with running Jupyter and installing whatever additional packages might be necessary. Instructions about these details will be circulated in advance of the lecture, but participants should be prepared to set up and/0r sign up for accounts in those environments before the lecture so that they are ready to run the hands-on exercises during the allotted time.