Past lectures and seminars

Summer term 2023

• Lecture Theoretical Computer Science 2: Computability and complexity theory for Bachelor Students
• Seminar Tuebingen AI Exhibition: maintenance and discourse for master students

Winter term 2022

• Lecture Theoretical Computer Science 1: Algorithms and Data Structures for Bachelor Students
• Practical Tuebingen AI exhibition for Master Students

Summer term 2022

• Lecture Statistical Machine Learning for Master Students
• Seminar Tuebingen AI exhibition for Master Students: an interdisciplinary seminar jointly with students and lecturers of anthropology

Summer term 2021

• Lecture Theoretical Computer Science: Theory of computation and complexity theory (BSc, 4+2 SWS)
• Research seminar "Machine Learning Theory" (runs constantly)

Winter term 2020/21

• Lecture Mathematics for Machine Learning (MSc, 4+2 SWS)
• Research seminar "Machine Learning Theory" (runs constantly)


• Summer term 2020:
  • Lecture Statistical Machine Learning (4+2 SWS, MSc)
• Summer term 2019:
  • In the context of the Cyber Valley Discussion in Tübingen: Seminar KI, Wissenschaft, Gesellschaft und Verantwortung: Ein interaktives Seminar zur Meinungsbildung, involving professors from computer science, political science, the school of law, economics, philosophy and ethics; open to all university students.
  • Statistical Machine Learning (Master CS, 4+2 SWS)
• Winter term 2018/19:
  • Algorithms (Bachelor CS, 4+2 SWS)
  • Statistical Network Analysis (Master CS, 2+2 SWS, by Debarghya Ghoshdastidar)
• Summer term 2018:
  • Machine Learning: Algorithms and Theory (4 + 2 SWS), lecture course for Master Students
  • Seminar Statistical Inference on Networks for Master students (2 SWS), taught jointly with Debarghya Ghoshdastidar
• Winter term 2017/18
  • Mathematik 1 for Bachelor Students (Bachelor CS, 4+2 SWS).
  • Seminar Ethik und Wissenschaftstheorie des maschinellen Lernens, joint seminar by Thomas Grote (Ethics), Philipp Berens, Ulrike von Luxburg, for Master students of diverse disciplines.
• Summer term 2017 Machine learning: theory and algorithms (Master students CS + Maths, 4+2 SWS).
• Winter term 2016/17
  • Mathematik 1 for Bachelor Students (Bachelor CS, 4+2 SWS)
  • Seminar: Machine Lerning Theory: Crowdsourcing algorithms and their statistical analysis (Master CS)
• Summer term 2016: Machine learning: algorithms and theory (Master CS and Maths, 4 + 2 SWS)
• Summer 2015: Statistical Learning Theory, course for the machine learning summer school, Tuebingen, Germany.
• Summer term 2015: Machine learning (Master CS and Maths, 4 + 2 SWS).
• Winter term 2014/15: Algorithms and Data Structures (Bachelor CS, 3+1 SWS)
• Summer term 2014: Machine learning (Master CS and Maths, 4 + 2 SWS).
• Winter term 2013/14: Algorithms and Data Structures (Bachelor CS, 3+1 SWS)
• Mathematical Theory of Machine Learning (Master Maths and CS, 2 SWS)
• Summer term 2013: Machine learning / algorithmic learning (Master CS and Maths, 4+2 SWS)
• Winter term 2012/13: Advanced algorithms (Master CS, 4+2 SWS)
• Summer term 2012: Seminar Machine Learning (Master CS, 2 SWS)
• Winter term 2011/12: Advanced Algorithms (Master CS, 4+2 SWS)
• Summer term 2011: "Unsupervised learning and the analysis of networks" (Master CS, 2+2 SWS)
• Winter term 2007/2008: "Mathematical theory of machine learning" at the Mathematics Department of the University of Tübingen
• Summer 2007: Course on "Clustering: Theory and Algorithms" at the Pascal Machine Learning Bootcamp, Barcelona, Spain
• Summer 2007: Practical Sessions on "Spectral Clustering and other graph based algorithms" at the Machine Learning Summer School, Tübingen, Germany. Matlab Graph Demo available here.
• Summer term 2006: "Unsupervised Learning", TU Darmstadt
• Winter term 2005/06: Seminar Machine Learning with Graphs, TU Darmstadt