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Python Seminar Course at UC Berkeley (AY 250)
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Python Computing for Data Science

An Undergraduate/Graduate Seminar Course at UC Berkeley (AY 250)

HFA B-1: Thursday 1 - 4 PM FALL 2013 (CCN #06080)


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.

Course Schedule

Date Content Leader
Aug 29 Advanced Python Language Concepts (geared towards Boot Camp graduates) Josh
Sep 5 scipy, numpy Fernando
Sep 12 Advanced versioning, application building (optparse), debugging & testing Josh
Sep 19 Advanced plotting, Notebooks and data vizualization, mayavi Fernando
Sep 26 Machine Learning Josh
Oct 3 Interacting with the world (xml-rpc, urllib, sending and receiving email, serial) Josh
Oct 10 Database interaction, large datasets (HDF5) Josh
Oct 17 Pandas and Timeseries Modelling Wes McKinney
Oct 24 GUI (Tkinter, GTK, Traits) Josh
Oct 31 Parallelism Paul/Fernando
Nov 7 Web frameworks & RESTful APIs, Flask Josh
Nov 14 Bayesian programming & Symbolic math Joey Richards
Nov 21 Cython; wrapper around legacy code -- FORTRAN, C, etc Paul
Nov 28 holiday
Dec 5/Onward final project work


Each Thursday 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 Monday morning before homeworks are due, 10am-12 in Evans 481. Email Josh with any questions if you cannot attend.


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

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