The workshop will take place tentatively on July 27, 2022, on Zoom and Youtube Livestreaming
About The Data Science Summer School
The Data Science Summer School is a series of theoretical and practical workshops on the exciting methods and technologies currently employed by industry, government, and civil society to address the world's most complex problems today. It is organized by the Hertie School Data Science Lab with funding and support from the Hertie School.
Widely considered as one of the best programming languages for beginners, Python is a general purpose language that is currently the best choice for machine learning and deep learning research and application. The course will walk you through the basics of this language and how to use it to solve programming challenges.
You can download the syllabus here
All workshop materials and recording are under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 license. You are free to share — copy and redistribute the material in any medium or format, and adapt — remix, transform, and build upon the material. However, you must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. You may not use the material for commercial purposes. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
- Course Github repository with code and data
- Solution to Exercise Notebook 1
- Solution to Exercise Notebook 2 (Check version 2)
Prof. Tom Paskhalis
Tom Paskhalis a computational political scientist and data scientist. Currently, he is an Assistant Professor in Political Science and Data Science at Trinity College Dublin, Department of Political Science. His methodological research interests include machine learning, Bayesian modelling, text analysis, record linkage and data visualisation
Schedule (Central European Summer Time - CEST)
Introduction to Python Programming (Part I)
Introduction to Python Programming (Part II)