Scientific Computing with Python
Austin, Texas • July 10-16, 2017
 

SciPy 2017 Tutorials Schedule

The SciPy Conference kicks off with two days of tutorials (July 10-11) that take place before the general conference. These sessions provide extremely affordable access to expert training, and consistently receive fantastic feedback from participants.

This year you can choose from 19 different SciPy tutorials. New to Python? Check out our Introductory Track: Software Carpentry Scientific Python Course (Parts 1 and 2) on July 10  followed by Numpy and Anatomy of Matplotlib on July 11.

07/10/2017
8:00 am - 12:00 pmSoftware Carpentry Scientific Python Course Part 1 (Beginner) [More Info]
Maxim Belkin, Software Carpentry
8:00 am - 12:00 pmCython for Data, Scientists, and Data Scientists (Intermediate/Advanced) [More Info]
Kurt Smith, HomeAway
8:00 am - 12:00 pmNumba: Tell Those C++ Bullies to Get Lost (Intermediate) [More Info]
Gil Forsyth, George Washington University
Lorena Barba, George Washington University
8:00 am - 12:00 pmAutomatic Code Generation with SymPy (Advanced) [More Info]
Jason Moore, PyDy and SymPy
Aaron Meurer, University of South Carolina, SymPy
8:00 am - 12:00 pmModern Optimization Methods in Python (Intermediate/Advanced) [More Info]
Michael McKerns, UQ Foundation
Noon-1:30 pmLunch Break
1:30 pm - 5:30 pmSoftware Carpentry Scientific Python Course Part 2 (Beginner) [More Info]
Maxim Belkin, Software Carpentry
1:30 pm - 5:30 pmComputational Statistics (Beginner) [More Info]
Allen Downey, Olin College
1:30 pm - 5:30 pmThe Jupyter Interactive Widget Ecosystem (Intermediate/Advanced) [More Info]
Matt Craig, Minnesota State University Moorhead
Sylvain Corlay
Jason Grout, Bloomberg LP
1:30 pm - 5:30 pmHDF5 take 2: h5py & PyTables (Intermediate/Advanced) [More Info]
Frank Willmore, HDF Group
1:30 pm - 5:30 pmInteractive data visualization with HoloViews & Bokeh (Advanced) [More Info]
Philipp Rudiger, Continuum Analytics
Jean-Luc Stevens, Continuum Analytics
Bryan Van de Ven, Continuum Analytics

07/11/2017
8:00 am - 12:00 pmIntroduction to numerical computing with NumPy (Beginner) [More Info]
Dillon Niederhut, Enthought
8:00 am - 12:00 pmPandas for Data Analysis (Beginner) [More Info]
Daniel Chen, Virginia Tech
8:00 am - 12:00 pmMachine Learning with scikit-learn Part One (Intermediate) [More Info]
Andreas Mueller, Columbia University
Alexandre Gramfort, INRIA, Université Paris-Saclay
8:00 am - 12:00 pmParallelizing Scientific Python with Dask (Intermediate) [More Info]
James Crist, Continuum Analytics
Martin Durant, Continuum Analytics
Skipper Seabold, Civis Analytics
8:00 am - 12:00 pmParallel Data Analysis in Python (Intermediate) [More Info]
Matthew Rocklin, Continuum Analytics
Ben Zaitlen, Continuum Analytics
Aron Ahmadia, Capital One
Noon-1:30 pmLunch Break
1:30 pm - 5:30 pmAnatomy of Matplotlib (Beginner) [More Info]
Ben Root, Atmospheric and Environmental Research, Inc/Matplotlib
1:30 pm - 5:30 pmscikit-image: image processing for Python (Intermediate) [More Info]
Stéfan van der Walt, University of California, Berkeley
Emmanuelle Gouillart
Claire McQuin, Broad Institute
1:30 pm - 5:30 pmNetwork Science and Statistics: Fundamentals and Applications (Intermediate) [More Info]
Eric Ma, MIT
1:30 pm - 5:30 pmMachine Learning with scikit-learn Part Two (Intermediate) [More Info]
Andreas Mueller, Columbia University
Alexandre Gramfort, INRIA, Université Paris-Saclay
1:30 pm - 5:30 pmSignal Processing and Communications Hands-On Using scikit-dsp-comm (Intermediate) [More Info]
Mark Wickert, University of Colorado