Curriculum · Hands-On RL · Bootcamps

Teaching & Training

Academic courses, graduate seminars, and international bootcamps taught at the University of Salzburg, blending deep mathematical foundations with hands-on computational implementations.

Bringing Reinforcement Learning to Salzburg

Coming from CERN, where I ran the first deep RL experiment on an accelerator, I introduced reinforcement learning into the teaching at the University of Salzburg in 2020: first as a seminar topic, then as dedicated courses, until it became a regular part of the curriculum.

  • WS 2020/21: first RL teaching, Topics in Data Science: Reinforcement Learning (SE 405.970).
  • SS 2021 and SS 2022: first dedicated course, Einführung in Deep Reinforcement Learning (UV 405.986), with CERN guest lectures.
  • SS 2023: Advanced Survey of Reinforcement Learning in the MSc Data Science and the DAS doctoral programme (DSM.105).
  • Since SS 2024: Reinforcement Learning lecture and exercise (VO 536.111 / UE 536.112) in the BSc Artificial Intelligence curriculum, taught every year.
  • SS 2026: Advanced Reinforcement Learning and Agentic AI Systems (DSM.110) in the MSc Data Science, also open to MSc Computer Science and DAS PhD students.
  • Beyond the curriculum: the International RL Bootcamp (since 2024), the monthly RL Coffee, and RL training for companies via DIH West.

Current Courses (2025/2026)

Reinforcement Learning (VO 536.111 + UE 536.112)

Core RL lecture and exercise of the BSc Artificial Intelligence: Markov decision processes, dynamic programming, Monte Carlo and temporal-difference learning, Q-learning, policy gradients and actor-critic methods, with hands-on implementations.

Undergraduate BSc AI curriculum RL
Advanced Reinforcement Learning and Agentic AI Systems (DSM.110)

Advanced course on current reinforcement learning and the design of autonomous AI agents capable of long-term planning and decision-making in complex environments.

Graduate MSc Data Science RL AI
Einführung in die KI: Grundlagen und Anwendung (KS 999.A65)

Introductory course on the foundations and applications of Artificial Intelligence, open to students of all programmes as a free elective.

Undergraduate Free elective AI

Earlier Courses

Einführung in Deep Reinforcement Learning (UV 405.986, SS 2021, SS 2022)

The first dedicated RL course at the University of Salzburg: DQN, policy gradients, actor-critic methods and team projects.

Graduate RL Deep Learning
Advanced Survey of Reinforcement Learning (DSM.105, SS 2023)

Research-oriented survey of model-based RL, meta-learning, safe RL and applications, with guest talks from CERN.

Graduate RL Research
Topics in Data Science: Reinforcement Learning (SE 405.970, WS 2020/21)

Seminar that introduced reinforcement learning to the data science programme in Salzburg.

Graduate Data Science RL
Precision Medicine (UV 405.976, WS 2021/22; DSM.107, SS 2023)

Mathematical and statistical foundations of precision medicine, including dynamic treatment regimes and reinforcement learning in healthcare.

Graduate Medicine Math

Teaching Philosophy

My teaching approach emphasizes the connection between theory and practice. I believe in:

Bootcamps & Workshops

Beyond regular courses, I organize intensive training programs:

3rd RL Bootcamp (2026)

International hands-on bootcamp at Unipark Nonntal, University of Salzburg (Sep 16–18, 2026). Custom Gym environments, model-based RL, actor-critics, and real-world transfer.

Upcoming Sep 2026

2nd RL Bootcamp (2025)

Intensive bootcamp held in Salzburg (Sep 17-19, 2025). Covered advanced policy gradients, actor-critic methods, and continuous control.

View 2025 Bootcamp

1st RL Bootcamp (2024)

Inaugural bootcamp bringing together students and researchers for hands-on RL training.

View 2024 Bootcamp

RL Coffee

Monthly informal meetup (first Friday of each month) for RL researchers and practitioners.

Join Us

RL4AA Workshops

International workshops on Reinforcement Learning for Autonomous Accelerators (CERN, DESY, KIT, SLAC).

Visit RL4AA