The workshop will take place on August 7, 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
How can you analyze large quantities of data? As soon as you consider tools like Linear Regression, Clustering, Network Analysis or Machine Learning, Linear Algebra is around the corner. Linear Algebra is a branch of mathematics that revolves around vectors and matrices. It helps to build efficient algorithms on massive datasets. This workshop will help you to develop an understanding for this key component of data science.
This workshop addresses students who never attended a Linear Algebra course. The aim is to present mathematical concepts which are a prerequisites for topics like Machine Learning and Causal Inference. The workshop will cover many practical examples using Linear Algebra to create and modify image data.
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. Kristian Rother
Dr. Kristian Rother is a professional Python and data science trainer with over a decade of experience teaching programming to researchers, scientists, and developers across Europe. With a background in molecular biology and bioinformatics, he brings scientific rigor to his interactive, hands-on workshops. Kristian is the co-founder of Academis and author of "Managing Your Biological Data with Python" and "Pro Python Best Practices". He specializes in making complex topics accessible, with a focus on clean code, testing, and practical data workflows.
Schedule (Central European Summer Time - CEST)
Session Starts
Linear Algebra for Data Science (Part I)
Short Break
Session Continues
Linear Algebra for Data Science (Part II)