Learning experiences that connect theory with practice
I teach statistics, machine learning, and causal inference with an emphasis on intuition, code, and applied storytelling—whether in the classroom, at conferences, or inside teams.
Flagship workshops
Programs designed for professionals and researchers who want to harness causal ML in their own contexts.
ZIB Academy 2024 · Causal Inference & ML
Participants explore Double Machine Learning end-to-end: from counterfactual thinking to model deployment. Includes live demos, collaborative coding, and case-based labs.
PyCon DE & PyData Berlin 2024
“Using ML to find out the Why?”—a hands-on tutorial guiding data scientists through causal framing, modeling pitfalls, and practical DoubleML workflows.
Finance Academy · Novartis AG
Digital Modelling Core (DMC) curriculum blending forecasting, machine learning, and business interpretation with exercises rooted in finance use cases.
University courses
I lead tutorials and seminars that help students internalize statistical reasoning and machine learning with modern tooling.
Bachelor level
Quantitative Risk Management
Decision theory, risk measures, stochastic dependencies, severity/frequency modeling, and simulation—grounded in economic examples.
Tutorials · 2024, 2025
Statistics I & II
Descriptive analytics, regression, time series, sampling theory, hypothesis testing, and multivariate modeling with applied datasets.
Tutorials · 2023 – 2025
Intro to Mathematics & Statistics in Economics
Bridging the gap into university-level rigor with supportive pacing, collaborative exercises, and confidence-building study strategies.
Tutorials · 2023, 2024
Master level
Seminar Large Language Models
Explores the fast-moving landscape of LLMs with experiments, deployment patterns, and connections to causal reasoning.
2024, 2025
Introduction to Deep Learning
Hands-on neural network projects across computer vision, time series, and generative models with an emphasis on business translations.
Tutorials · 2024, 2025, 2026
Statistical Programming with Python
Hypothesis testing, regression, and classification in Python—pairing morning lectures with afternoon lab sessions.
Tutorials · 2024, 2025, 2026
Seminar Causal Machine Learning
Modern causal inference toolkits for economic applications, featuring DoubleML, simulation-based intuition, and reproducible codebases.
2024
Machine Learning in Economics & Business
R-centered labs covering Lasso, boosting, neural nets, and their role in structural modeling and policy evaluation.
Tutorials · 2023
Seminars in BA & DL/ML
Guiding students through cutting-edge research, critical discussion, and presentation craft in analytics and deep learning.
2023
Invite me to teach
Let’s design a session tailored to your team or conference—hands-on, inclusive, and immediately applicable.