Python is becoming the de facto superglue language for modern scientific computing. In this course we will learn Pythonic interactions with databases, imaging processing, advanced statistical and numerical packages, web frameworks, machine-learning, and parallelism. Each week will involve lectures and coding projects. In the final project, students will build a working codebase useful for their own research domain.

This class is for any student working in a quantative discpline and with familiarily with Python. Those who completed the Python Bootcamp or equivalent will be eligible.

Each Monday we will be introducing a resonably self-contained topic with two back-to-back lectures. In between a short (~20 minute) breakout coding session will be conducted. Homeworks will require you to write a large (several hundred line) codebase.

There will be a regular help session every Friday morning before homeworks are due, 10am-12 in Evans 481. Email Isaac with any questions if you cannot attend.

Email us at [email protected] or contact the professor directly ([email protected]). You can also contact the GSI, Isaac, at ([email protected]. Auditing is not permitted by the University but those wishing to sit in on a class or two should contact the professor before attending.