The workshop will take place tentatively on August 15, 2023, 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 and the Dieter Schwarz Foundation

Workshop Details

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.

Content Licensing

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.

Workshop Materials


Musashi Jacobs-Harukawa
Musashi Jacobs-Harukawa

Musashi Jacobs-Harukawa is a Postdoctoral Research Associate with Data Driven Social Science Initiative, Prince University, where he works on applied machine learning and computational social science methodology. His specific interests are in text, measurement, and explanation. Prior to joining DDSS, Musashi was a pre-doctoral researcher at University College London, where he worked with Dr Lucy Barnes on the Mental Models of the Political Economy project. He received his DPhil in Politics from the University of Oxford, where he wrote his thesis on novel applications of machine learning to the study of political campaigns.

Schedule (Central European Summer Time - CEST)

Session Starts

Introduction to Python Programming (Part I)

Short Break

Session Continues

Introduction to Python Programming (Part II)

Session Ends

Watch Recording