Tutorials last either 90 minutes or 180 minutes. In the latter case, they are split in two sessions.
The exact hours are subject to change to account for the logistics of coffee and lunch breaks.
| Time | Introductory | Advanced | Applications |
|---|---|---|---|
| 9:00 | Introduction to Jupyter, M. Muller | Advanced Python constructs for scientists and engineers, Pietro Berkes | Doing bioinformatics with scikit-bio and BioPython, Joris Vankerschaver |
| 11:00 | Introduction to Python, M. Rastgoo & G. Lemaitre | Databases for scientists, A. Hendorf | Geospatial data I |
| 14:00 | Introduction to Python, M. Rastgoo & G. Lemaitre | From exploratory computing to performances, a tour of Python profiling and optimization, A. Ingargiola | Geospatial data II |
| 16:00 | NumPy I, G. Ingold | Privacy for Data Scientists, Katharine Jarmul | Topic Modelling, Parul Sethi |
| Time | Introductory | Advanced | Applications |
|---|---|---|---|
| 9:00 | NumPy II, G. Ingold | The Hitchhiker's Guide to Parallelism with Python, D. Valters | Advanced machine learning, Y. Peleg |
| 11:00 | Matplotlib, Alexandre de Siqueira | Parallel Data Analysis with Dask, Ian Stokes Rees | Understanding and diagnosing your machine-learning models, G. Varoquaux |
| 14:00 | Pandas, TBA | Data visualization -- from default and suboptimal to efficient and awesome, B. Gorelik | Deep Diving into GANs: From Theory to Production Michele De Simoni, Paolo Galeone |
| 16:00 | Scipy, TBA | CFFI, Ctypes, Cython: the Good, the Bad and the Ugly, M. Picus | Deep Learning in Python using Chainer, C. Loomis |