Tutorial Participant Instructions
Contact scipy@enthought.com if you need an invitation to Slack.
Monday July 11, 2016 - Tuesday July 12, 2016 8:00 AM - 5:00 PM
Software Carpentry Instructor - Training Room 108
Ariel Rokem, Software Carpentry
Greg Wilson, Software Carpentry
Tutorial materials including an outline can be viewed here
Also, please read the following articles before the start of the tutorial:
- Why Programming is Hard to Teach
- Top 10 Myths About Teaching Computer Science
- Success in Introductory Programming: What Works?
Monday July 11, 2016 8:00 AM - 12:00 PM
Network Science and Statistics: Fundamentals and Applications (Intermediate) Room 203Eric Ma, MIT
Tutorial materials including an outline can be viewed here
Deep Learning for Image Recognition (Beginner) Room 105
Bargava Subramanian
Tutorial materials including an outline can be viewed here
Installation instructions may be viewed here
NumPy (Beginner) Room 106
Alexandre Chabot-LeClerc, Enthought
Tutorial materials including an outline can be viewed here
Symbolic Compution with Python using SymPy (Beginner) Room 103
Ondřej Čertík, Los Alamos National Laboratory
Amit Kumar, Delhi Technological University, India
Jason Moore, Lead Developer, PyDy
Aaron Meurer
Sartaj Singh, IIT BHU
Harsh Gupta, IIT Kharagpur
Tutorial materials including an outline can be viewed here
Software Carpentry Scientific Python Course Parts 1 and 2(Beginner) Room 101
Matthias Bussonnier, Jupyter/Ipython, University of California, Berkeley
Matt Davis
Jessica Hamrick, University of California, Berkeley
Ted Hart
Kathryn Huff, Fellow, University of California, Berkeley
Greg Wilson, Software Carpentry
Tutorial materials including an outline can be viewed here
Monday July 11, 2016 1:30 pm - 5:30 PM
Bokeh for Data Applications and Visualization (Intermediate) Room 203Bryan Van de Ven, Continuum Analytics
James A. Bednar, University of Edinburgh and Continuum Analytics
Tutorial materials including an outline can be viewed here
Simulating Robot, Vehicle, Spacecraft, and Animal Motion with Python (Advanced) Room 103
Jason Moore, Lead Developer, PyDy
Robert McMurry, University of California, Davis
Brandon Milam, University of Florida, Gainsville
Tutorial materials including an outline can be viewed here
Data Science is Software: Developer #lifehacks for the Python Data Scientist (Intermediate) Room 106
Peter Bull, DrivenData
Isaac Slavitt, DrivenData
Tutorial materials including an outline can be viewed here
Setup instructions can be viewed here
Numba: Tell those C++ bullies to get lost (Intermediate) Room 105
Lorena Barba, George Washington University
Gil Forsyth
Tutorial materials including an outline can be viewed here
Software Carpentry Scientific Python Course Part 2 (Beginner) Room 101
See above
Tuesday July 12, 2016 8:00 AM - 12:00 PM
Time Series Analysis with Python (Intermediate) Room 203
Aileen Nielsen
Tutorial materials including an outline can be viewed here
Machine Learning with scikit-learn Parts 1 and 2 (Intermediate) Room 105
Andreas Mueller
Sebastian Raschka
Tutorial materials including an outline can be viewed here
Matplotlib Tutorial (Beginner) Room 101
Nicolas Rougier, INRIA Bordeaux Sud-Ouest, Talence, France, Neurodegenerative Diseases Institute, University of Borde
Tutorial materials including an outline can be viewed here
Test script here
Parallel Python: Analyzing Large Datasets (Intermediate) Room 106
Matthew Rocklin, Continuum Analytics
Min RK, University of California, Berkeley
Ben Zaitlen, Continuum Analytics
Tutorial installation materials can be viewed here
Network Science and Statistics: Fundamentals and Applications (Intermediate) Room 103
Eric Ma, MIT
Tutorial materials including an outline can be viewed here
Tuesday July 12, 2016 1:30 pm - 5:30 PM
Scikit-image: Image analysis in Python (Intermediate) Room 106
Stefan van der Walt, University of California, Berkeley
Andreas Mueller, New York University Center for Data Science
Juan Nunez-Iglesias, University of Melbourne
Tutorial materials including an outline can be viewed here
Machine Learning with scikit-learn Part 2(Intermediate) Room 105
Andreas Mueller
Sebastian Raschka
See above
Analyzing and Manipulating Data with Pandas (Beginner) Room 203
Jonathan Rocher, KBI BioPharma
Tutorial materials including an outline can be viewed here
Scalable Hierarchical Parallel Computing (Intermediate) Room 101
Michael McKerns, UQ Foundation
Tutorial materials including an outline can be viewed here
Geographic Data Science with PySAL and the pydata stack (Beginner) Room 103
Serge Rey, Arizona State University
Dani Arribas-Bel, University of Liverpool
Tutorial materials including an outline can be viewed here
Installation instructions can be viewed here
