The workshop will take place on August 8, 2025, 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
An absolute must-have knowledge for data scientists is statistics and probability. They gives us the language and tools to quantify the uncertainty of events and reason in a principled manner. Machine learning is about developing predictive models from uncertain data, with imperfect or incomplete information. We can manage this uncertainty using the theories and tools of these two disciplines.
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
To be updated
Instructor
Dr. Darina Goldin
Dr. Darina Goldin is a Principal Data Scientist based in Berlin, specialising in machine learning for sports and esports. With a Ph.D. in Control Science from TU Berlin, she has led the data science efforts at Bayes Esports since its early days, developing live-odds prediction systems and mentoring fellow data scientists . Recognized as an Accredited Expert in Data Science & ML by AI Guild, Darina combines deep technical insight with real-world ML applications. Outside work, she's a competitive Brazilian Jiu‑Jitsu athlete, even qualifying for the World Combat Games - bringing the same discipline and analytical mind to both her sport and her data-driven projects.
Schedule (Central European Summer Time - CEST)
Session Starts
Statistics and Probability for Data Science (Part I)
Short Break
Session Continues
Statistics and Probability for Data Science (Part II)