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DSF > Teaching

Teaching Activities of the Institute

Autumn School 2026

Machine Learning I

Lecturer: Nihat Ay & Frank Röder

  • Monday, September 14, 2026
    •  9:00 - 10:30: Lecture 1, Building M, Room 0.526
    • 10:45 - 12:15: Lecture 2, Building M, Room 0.526
    • 12:15 - 13:15: Break
    • 13:15 - 16:30: Self-study
  • Tuesday, September 15, 2026
    •  9:00 - 10:30: Lecture 3, Building M, Room 0.526
    • 10:45 - 12:15: Lecture 4, Building M, Room 0.526
    • 12:15 - 13:15: Break
    • 13:15 - 14:45: T1/T1, Building M, Room 0.526/1.582
    • 15:00 - 16:30: P1/T1, Building M, Room 0.526/1.582
  • Wednesday, September 16, 2026
    • Self-study
  • Thursday, September 17, 2026
    •  9:00 - 10:30: Lecture 5, Building M, Room 0.526
    • 10:45 - 12:15: Lecture 6, Building M, Room 0.526
    • 12:15 - 13:15: Break
    • 13:15 - 14:45: T2/T2, Building M, Room 0.526/1.582
    • 15:00 - 16:30: P2/T2, Building M, Room 0.526/1.582
  • Friday, September 18, 2026
    • Self-study
  • Monday, September 21, 2026
    •  9:00 - 10:30: Lecture 7, Building M, Room 0.526
    • 10:45 - 12:15: Lecture 8, Building M, Room 0.526
    • 12:15 - 13:15: Break
    • 13:15 - 14:45: T3/T3, Building M, Room 0.526/1.582
    • 15:00 - 16:30: P3/T3, Building M, Room 0.526/1.582
  • Tuesday, September 22, 2026
    • Self-study
  • Wednesday, September 23, 2026
    •  9:00 - 10:30: Lecture 9, Building M, Room 0.526
    • 10:45 - 12:15: Lecture 10, Building M, Room 0.526
    • 12:15 - 13:15: Break
    • 13:15 - 14:45: T4/T4, Building M, Room 0.526/1.582
    • 15:00 - 16:30: P4/T4, Building M, Room 0.526/1.582
  • Thursday, September 24, 2026
    • Self-study
  • Friday, September 25, 2026
    •  9:00 - 10:30: Lecture 11, Building M, Room 0.526
    • 10:45 - 12:15: Lecture 12, Building M, Room 0.526
    • 12:15 - 13:15: Break
    • 13:15 - 14:45: T5/T5, Building M, Room 0.526/1.582
    • 15:00 - 16:30: P5/T5, Building M, Room 0.526/1.582
  • Monday, September 28, 2026
    •   Self-study
  • Tuesday, September 29, 2026
    •  9:00 - 10:30: Lecture 13, Building M, Room 0.526
    • 10:45 - 12:15: Lecture 14, Building M, Room 0.526
    • 12:15 - 13:15: Break
    • 13:15 - 14:45: T6/T6, Building M, Room 0.526/1.582
    • 15:00 - 16:30: P6/T6, Building M, Room 0.526/1.582
  • Wednesday, September 30, 2026
    • Self-study
  • Thursday, October 1, 2026
    • Self-study
  • Friday, October 2, 2026
    •  9:00 - 12:15 Written Exam, Building D, 2.022

 

 

Summer term 2026

Machine Learning I
  • Lecture: Nihat Ay
  • Exercise: Manfred Eppe & Jesse van Oostrum & Frank Röder
  • Lecture: Wednesday: 09:45 - 11:15, Building H, Audimax I
  • Exercise:
    • Monday: 09:45 - 11:15, Building D, Room 1.024
    • Monday: 11:30 - 13:00, Building D, Room 1.024
    • Tuesday: 09:45 - 11:15, Building D, Room 1.023
    • Tuesday: 11:30 - 13:00, Building D, Room 1.023
Information Geometry
  • Lecture: Nihat Ay
  • Exercise: Pradeep Kumar Banerjee & Adwait Datar
  • Lecture: Friday: 09:45 - 11:15, Building I, Audimax II
  • Exercise:
    • Tuesday: 14:00 - 15:30, Building A, Room 2.34
    • Wednesday: 11:30 - 13:00, Building N, Room 0.009
Deep Reinforcement Learning
  • Organiser: Pradeep Kumar Banerjee & Frank Röder
  • Tuesday, 11:00 - 12:30
  • Location: HipOne, Room 5.002
Causal Machine Learning

Organiser: Jesse  van Oostrum & Leon Sierau

Wednesday,14:30 - 16:00

Location: HipOne, Room 5.002

Winter term 2025/2026

Machine Learning II
  • Lecture: Adwait Datar & Frank Röder
  • Exercise: Adwait Datar & Frank Röder
  • Lecture: Thursday: 09:45 - 11:15, Building H, Room 0.16
  • Exercise:
    • Wednesday: 09:45 - 11:15, Building H, Room 0.01
    • Wednesday: 11:30 - 13:00, Building H, Room 0.01
    • Thursday: 11:30 - 13:00, Building H, Room 0.03
Reinforcement Learning
  • Lecture: Manfred Eppe & Frank Röder
  • Exercise: Manfred Eppe & Frank Röder
  • Lecture: Monday: 09:45 - 11:15, Building HS28, Room 1.007
  • Exercise: Monday: 11:30 - 13:00, Building HS28, Room 1.007

Summer term 2025

Machine Learning I
  • Lecture: Nihat Ay
  • Exercise: Nihat Ay & Manfred Eppe
  • Lecture: Wednesday: 09:45 - 11:15, Building K, Room 0506
  • Exercise:
    • Monday: 09:45 - 11:15, Building N, Room 0009
    • Monday: 11:30 - 13:00, Building N, Room 0007
    • Tuesday: 09:45 - 11:15, Building D, Room 1.023
    • Tuesday: 11:30 - 13:00, Building D, Room 1.023
Statistical Models
  • Lecture: Nihat Ay & Matthias Schulte
  • Exercise: Nihat Ay & Matthias Schulte
  • Lecture:
    • Tuesday: 13:15 - 14:45, weekly, Building D, Room 2.022
    • Thursday: 15:00 - 16:30, fortnightly, Building D, Room 2.022
  • Exercises: Thursday: 15:00 - 16:30, fortnightly, Building D, Room 2.022
Deep Generative Models
  • Organiser: Pradeep Kumar Banerjee
  • Tuesday, 11:30 - 13:00
  • Location: HIP One, Room 5.002
Deep Reinforcement Learning
  • Organiser: Pradeep Kumar Banerjee
  • Tuesday, 14:00 - 15:30
  • Location: HIP One, Room 5.002
Introduction to Reinforcement Learning
  • Organiser: Manfred Eppe
  • Thursday, 11:00 - 12:30
  • Location: HIP One, Room 5.002

Winter term 2024/2025

Machine Learning II
  • Lecture: Nihat Ay & Manfred Eppe
  • Exercise: Nihat Ay & Manfred Eppe & Adwait Datar
  • Lecture: Wednesday: 09:45 - 11:15, Building K, Room 0506
  • Exercise:
    • Tuesday: 09:45 - 11:15, Building H, Room 0.007
    • Thursday: 11:30 - 13:00, Building H, Room 0.02
Das Kino-Seminar: Können Maschinen Mensch sein?
  • Organisers: Nihat Ay & Pradeep Kumar Banerjee
  • Tuesday, 12:30 - 14:00
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
Causal Inference in Machine Learning
  • Organisers: Nihat Ay & Carlotta Langer
  • Wednesday, 12:30 - 14:00
  • Location: Building D, Room D-1.023
Large Language Models and Information Theory: Decoding Words and Bits
  • Organiser: Pradeep Kumar Banerjee
  • Monday, 14:00 - 15:30
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002

Summer term 2024

Machine Learning I
  • Lecture: Nihat Ay
  • Exercise: Nihat Ay & Manfred Eppe & Adwait Datar
  • Lecture: Wednesdays, 09:45 – 11:15, Room K – 0506
  • Tutorials:
    • Group 1: Monday, 09:45 – 11:15, Room N – 0.009
    • Group 2: Monday, 11:30 – 13:00, Room N – 0.009
    • Group 3: Tuesday, 09:45 – 11:15, Room D – 1.023
    • Group 4: Tuesday, 11:30 – 13:00, Room D - 1.023
  • More Info: Stud.IP
Statistical Models
  • Lecture: Nihat Ay & Matthias Schulte
  • Exercise: Nihat Ay & Matthias Schulte
  • Lecture:
    • Tuesday: 13:15 - 14:45, weekly, Building D, Room 2.022
    • Thursday: 15:00 - 16:30, fortnightly, Building D, Room 2.022
  • Exercises: Thursday: 15:00 - 16:30, fortnightly, Building D, Room 2.022
Introduction to Reinforcement Learning
  • Organiser: Manfred Eppe
  • Wednesday, 11:30 – 13:00 (twice a month)
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • More Info: PDF, Stud.IP
Introduction to Deep Learning
  • Organiser: Pradeep Banerjee
  • Tuesdays, 11:30 – 13:00 
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • More Info: Stud.IP
Deep Reinforcement Learning
  • Organiser: Pradeep Banerjee
  • Tuesdays, 14:00 - 15:30 
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • More Info:  Stud.IP

Winter term 2023/2024

Machine Learning II
  • Lecture: Nihat Ay
  • Exercise: Nihat Ay & Manfred Eppe
  • Lecture: Fridays, 13:15 – 14:45, Room K – 0506
  • Exercise:
    – Calculation of the Exercises: Thursdays, 9:45 – 11:15, Room N – 0.008
    – Mathematical Questions & Answers: Thursdays, 11:30 – 13:00, Room D – 1.025
  • More Info: Stud.IP
Das Kino-Seminar: Können Maschinen Mensch sein?
  • Organiser: Nihat Ay 
  • Wednesdays, 11:30 – 13:00
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • More Info: Stud.IP
Causality in Machine Learning
  • Organisers: Pradeep Banerjee & Carlotta Langer
  • Tuesdays, 11:30 – 13:00 (every 2 weeks)
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • More Info:  Stud.IP
Large Language Models and Information Theory: Decoding Words and Bits
  • Organisers: Pradeep Banerjee & Jesse van Oostrum
  • Tuesdays, 14:00– 15:30 (every 2 weeks)
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • More Info: Stud.IP

Summer term 2023

Machine Learning I
  • Lecture: Nihat Ay
  • Exercise: Nihat Ay & Manfred Eppe & Adwait Datar
  • Lecture: Wednesdays, 09:45 – 11:15, Room K – 0506
  • Tutorials:
    – Group 1: Wednesdays, 11:30 – 13:00, Room H – 0.01
    – Group 2: Thursdays, 09:45 – 11:15, Room A – 0.01
    – Group 3: Thursdays, 11:30 – 13:00, Room D – 0.011
  • More Info: Stud.IP
Mensch und Maschine – Herausforderungen durch Künstliche Intelligenz
  • Organiser: Nihat Ay
  • Thursdays, 15:30 – 16:30
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • More Info: PDF, Stud.IP
Introduction to Reinforcement Learning
  • Organiser: Manfred Eppe
  • Tuesdays, 11:30 – 15:00
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • More Info: PDF, Stud.IP

Winter term 2022/2023

Machine Learning II
  • Lecture: Nihat Ay
  • Exercise: Nihat Ay & Manfred Eppe
  • Lecture: Tuesdays, 15:00 – 16:30, Room K – 0506
  • Exercise:
    – Calculation of the Exercises: Thursdays, 9:45 – 11:15, Room O – 0.007
    – Mathematical Questions & Answers: Thursdays, 11:30 – 13:00, Room A – 1.16
  • More Info: Stud.IP
Das Kino-Seminar: Können Maschinen intelligent sein?
  • Organisers: Nihat Ay & Manfred Eppe
  • Wednesdays, 11:30 – 13:00
  • Location: Blohmstraße 15 (HIP One), 5th Floor, Room 5.002
  • More Info: PDF, Stud.IP
Introduction to Data Science
  • Organisers: Manfred Eppe, Tobias Knopp, Matthias Schulte, Stefan Schulte und Dominik Schallmoser
  • Fridays, 13:15 – 14:45
  • Location: D – 2.022
  • more Info:PDF, Stud.IP

Summer term 2022

Machine Learning I
  • Nihat Ay, Manfred Eppe & Csongor Várady
  • lecture & exercise for Data Science (DSBS)
  • lecture: Wednesdays, 9:45 – 11:15, Room K – 0506
  • exercise:
    – Group 1: Thursdays, 9:45 – 11:15, Room A – 0.01
    – Group 2: Thursdays, 11:30 – 13:00, Room D – 0.011
    – Group 3: Tuesday, 11:30 – 13:00, Room A – 0.14
  • electronic exam: September 14th, 2022
  • more Info: Stud.IP

Winter term 2021/2022

Generieren von Strukturen in Bildern – Die Gibbs-Sampling-Methode (student team project)
  • Organisers: Nihat Ay & Csongor Várady
  • Student team project for Informatik-Ingenieurwesen (IIW)
  • more info: PDF
  • Timetable: PDF
Das Kino-Seminar: Können Maschinen intelligent sein?
  • Organiser: Nihat Ay
  • Thursdays, 11:30 – 13:00
  • Location: Blohmstraße 15 (HIP One), 5. Stock, Raum 5.002
  • more info: PDF, Stud.IP
  • Timetable: PDF

Summer term 2021

Gradientenmethoden in der Lerntheorie (Seminar)
  • Organiser: Nihat Ay
  • Masterstudierende ECTS-Punkte: 3

The following courses and seminars took place at the Max Planck Institute for Mathematics in the Sciences and the Leipzig University.

Winter term 2020/2021

Kernel Methods in Learning Theory
Recent Developments Towards a New Theory of Generalisation (Seminar)

Summer term 2019

Artificial Neural Networks and Machine Learning: Theoretical Foundations II
  • Nihat Ay
  • Thursdays, 11:15 – 12:45
  • Location: MPI MiS, A3 02
  • more info

Winter term 2018/2019

Artificial Neural Networks and Machine Learning: Theoretical Foundations I

Summer term 2017

Information Theory II
  • Nihat Ay
  • Tuesdays, 11:00 – 12:30
  • Location: MPI MiS, A3 02

Winter term 2016/2017

Information Theory I
  • Nihat Ay
  • Tuesdays, 11:00 – 12:30
  • Location: MPI MiS, A3 02

Summer term 2016

Grundlagen der Robotik und Seminar Morphological Computation
  • Keyan Ghazi-Zahedi
  • Tuesdays, 13:00 – 15:00
  • Location: University Leipzig, SG 2-14

Summer term 2015

Reinforcement Learning – An Introduction
  • Keyan Ghazi-Zahedi
  • Thursdays, 10:15 – 11:45
  • Location: A2, MPI MiS

Winter term 2014/2015

Geometric Aspects of Graphical Models and Neural Networks
  • Nihat Ay, Guido Montufar
  • Wednesdays, 10:15 – 11:45; first on November 26th
  • Location: A2, MPI MiS

Summer term 2013

Information Theory II
  • Nihat Ay
  • Wednesdays, 11:30 – 13:00; first on April 17th
  • Location: A2, MPI MiS

Winter term 2012/2013

Information Theory
  • Nihat Ay
  • Wednesdays, 11:00 – 12:30; first on October 10th
  • Location: A2, MPI MiS

Winter term 2011/2012

Second part of the IMPRS Ringvorlesung “Higher Dimensions”
  • Nihat Ay
  • Date: 9.,23.,30. November and 7., 14. December

Winter term 2010/2011

Stochastische Prozesse
  • Nihat Ay
  • Thursdays, 15:15 – 16:45, Hs 15
Optimierung und Komplexität
  • Nihat Ay

Summer term 2010

Stochastic Differential Equations
  • Nihat Ay
  • It will take place on Wednesdays, starting April 14, at 10:15 in A1.

Summer term 2009

Mathematical Learning Theory and Neural Networks
  • Nihat Ay

Summer term 2007

Concepts of Causality in Biology and Medicine (Seminar)
  • Korbinian Strimmer & Nihat Ay
Quantum Mechanics: basic mathematical structures and their operational interpretation
  • Arleta Szkola

Winter term 2006/2007

Information Theory II
  • Arleta Szkola
Random Graphs – New Developments Beyond the Erdös-Renyi Model
  • Tyll Krüger

Summer term 2006

Information Theory I
  • Arleta Szkola
Graphical Models and Causality
  • Nihat Ay
TU Hamburg
Institute for
Data Science Foundations
Blohmstraße 15
21079 Hamburg
E-mail : dsf-office@tuhh.de
Phone : +49 40 306 01 4932
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