Python for Scientific Programming on Friday, August 25, 9:00-5:00 pm

Dear Colleagues,

Please circulate this announcement among undergraduate students, graduate students, postdocs, and faculty/staff who are interested in learning about Python through the use of interactive Juptyer Notebooks. Faculty who are interested in incorporating more scientific computation/programming into their courses are particularly encouraged to attend to see how easy it can be with Jupyter Notebooks.

Are you interested in learning about Python? You should be. For aspiring Data Scientists, Python is probably the most important language to learn because of its rich ecosystem. Moreover, as curricula are modernized, Python and Jupyter Notebooks are quickly becoming essential in the education and training of students faced with entering a globally competitive workforce.

Through a CFD Teaching Enhancement Grant, the Center for Computational Mathematics is hosting a short course on using Python for scientific programming on Friday, August 25, 2017 from 9 a.m. – 5 p.m. in the Student Commons Building Room 1600. There will be several short breaks with coffee and light refreshments throughout the day, and lunch will be provided to all participants.

The course is intended for those that are new to Python or those that want a refresher on the basics. No prior programming experience is assumed.

We will use Jupyter Notebooks to provide a fun and interactive lecture environment where participants will be able to run, edit, and test code in real-time within a web browser. Participants will learn about variables, arrays, essential scientific libraries, plotting in 2- and 3-dimensions, loops, and even how to create their own user-defined functions/modules.

Space is limited, so please sign up using the form linked to below. The form takes about one minute to fill out.

Participants are expected to bring their own laptops and setup their laptops prior to the short course. Instructions on how to setup your laptop before the short course will be sent the week before the course.